THE NELSON MANDELA AFRICAN INSTITUTION OF SCIENCE AND
TECHNOLOGY (NM-AIST)
COVERAGE IMPROVEMENTS FOR MOBILE COMMUNICATION
IN RURAL AREAS OF TANZANIA
Adolph Kasegenya
A Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree of
(Masters of Science in Information and Communication Science and Engineering) of the
Nelson Mandela African Institution of Science and Technology.
Arusha, Tanzania.
October, 2014
i
ABSTRACT
This dissertation looks at how network operators operate in Tanzania. It examines how they set
up their networks, and the services offered so far. First thing first was to evaluate the Quality of
Services (QoS) offered by telecommunications network vendors in Lake Zone and to access their
coverage ranges. The assessments were done through a keen feasibility study of the selected area
done in Mwanza region as a study area, followed by the drive test field measurements performed
by the help of TEMS Investigation tools and software, the log files collected were evaluated by
using both Map Info software and Actix Analyzer. The study shows only 24.02% of the sample
area had a good coverage, while the poor coverage beyond threshold was recorded at 23.24%.
Also, when it comes to the case of QoS, it was observed that only 27.61% had a good QoS, while
the poor threshold was 2.76% of the entire sample area. This analysis was done in both rural and
urban areas, moreover the other aspect of this dissertation was to assess the planning and
optimization phases of the telecommunication networks done by the vendors and looked at the
conducive environment for Base Station Installation and it was done with the help of Map Info,
Asset, Google Earth and Measurements Reading Reports (MRR) tool. The Third generation (3G)
Planning was done for both coverage and capacity in Wideband Code Division Multiple Access
(WCDMA), which resulted into a better coverage with good performance of QoS and also
Optimization was done for power control mechanism to increase coverage through better
Received Signal Code Power (RSCP) value, better QoS through good ration of Received Power
to Noise (Ec/No) value. Lastly, different wireless technology services offered by
telecommunication vendors were evaluated based on their coverage and suggestions on how to
improve them were given out.
ii
DECLARATION
I, Adolph Kasegenya do hereby declare to the Senate of Nelson Mandela African Institution of
Science and Technology that this dissertation is my own original work and that it has neither
been submitted nor being concurrently submitted for degree award in any other institution.
_________________________________________ ________________
Name and signature of candidate Date
The above declaration is confirmed
________________________________________ _________________
Name and signature of supervisor1 Date
iii
COPYRIGHT
This dissertation is copyright material protected under the Berne Convention, the Copyright Act
of 1999 and other international and national enactments, in that behalf, on intellectual property.
It must not be reproduced by any means, in full or in part, except for short extracts in fair
dealing; for researcher, private study, critical scholarly review or discourse with an
acknowledgement, without a written permission of the Deputy Vice Chancellor for Academic,
Research and Innovation, on behalf of both the author and the Nelson Mandela African
Institution of Science and Technology.
iv
CERTIFICATION
The undersigned certify that they have read and hereby recommend for acceptance by the Nelson
Mandela African Institution of Science and Technology a dissertation entitled: Coverage
Improvements for Mobile Communication in Rural Areas of Tanzania, in fulfilment of the
requirements for the degree of Master of Science (Information and Communication Science and
Engineering (ICSE)) of the Nelson Mandela African Institution of Science and Technology.
...........................................................
Dr. Anael Sam
(Principal Supervisor)
Date: …………………………….
v
ACKNOWLEDGEMENT
I’m so grateful to Almighty God for giving me life, health and for his mighty doings in my life. I
express my heartfelt gratitude to my Supervisor at the Nelson Mandela African Institution of
Science and Technology (NMAIST), Dr. Anael Sam for his knowledge, experience, expertise,
valuable suggestions and comments, effective support where I couldn’t find an answer by
myself, gratitude to all the staff of school of Computation and Communication Science and
Engineering (CoCSE) since has there been providing valuable support whenever I needed it.
Then my gratitude goes to the management of NMAIST, for all the material and financial
support during course work and research, I have nothing to repay you, but am praying for the
name of NMAIST to fly high and the sky to be its limit towards the success of its mission and
vision.
I Wish also to thank my supervisor at Tigo company, Mr. Steven Katamba for allowing me to
use their resources during my research whenever I needed them. Also, I can’t forget Mr. Rodgers
Bajungu who was another supervisor in my side from Tigo. We work daily with him and he was
ready to help whenever I needed it. Thank you very much. Also, all Tigo staff in the department
of Planning just to mention few, Mr. Gasper Clement, Mr. Exaud Sudda and Mr. Raymaker
Sadick for working hand with hand and always gave me the support I needed despite of their
busy schedule. It was great working with such nice people and high level professionals in this
field of communication. I wish all of you all the best in your professional careers and in your
personal life. You have been such great friends. Thank you all very much.
May I express my gratitude to all my classmates, including Mr. Josia Nombo (PhD student), for
standing there with me during my two years of study here at NMAIST. They were so nice
provided me with all necessary help whenever I stumble through academic and life obstacles. Be
vi
blessed all. I’ll miss you very much. They were friends at times and also parents in another way
for whatever they thought it was beneficial to my life. Am forever indebted to you all.
And last but not least, I want to thank my family for the support and such great understanding to
allow me to perform my master’s study, being patient when they needed me and For encouraging
me to pursue higher goals and the dreams of my life with their moral and material support.
May the Almighty God bless you all abundantly.
Adolph kasegenya
October, 2014
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DEDICATION
This work is dedicated to Mrs. Regina Kasegenya and the late Mr. Aloyce Paul Kasegenya for
believing in me and providing all the necessary support through high moral standards, ethics,
and prayers which kept me going always. Also to all my family members for understanding and
supporting me in every way they can.
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TABLE OF CONTENTS
ABSTRACT ..................................................................................................................................... i
DECLARATION ............................................................................................................................ ii
COPYRIGHT ................................................................................................................................. iii
CERTIFICATION ......................................................................................................................... iv
ACKNOWLEDGEMENT .............................................................................................................. v
DEDICATION .............................................................................................................................. vii
CHAPTER ONE: GENERAL INTRODUCTION ...................................................................... 3
1. Introduction ............................................................................................................................. 3
1.1. Background Information .......................................................................................................... 5
1.2. Research problem and justification of study ............................................................................ 6
1.2.1. Research Problem ................................................................................................................. 6
1.2.2. Research Justification ........................................................................................................... 6
1.3. Objectives ................................................................................................................................ 7
1.3.1. General objective .................................................................................................................. 7
1.3.2. Specific objectives ................................................................................................................ 7
1.4. Hypotheses/Research questions ............................................................................................... 7
1.6. Research methodology ........................................................................................................... 10
1.6.1. Analysis of Quality of Service (QoS) ................................................................................. 10
1.6.2. Site Selection ...................................................................................................................... 11
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1.6.3. Planning and Optimization ................................................................................................. 11
CHAPTER TWO: REVIEW OF SCHEMES FOR ANALYZING QUALITYOF SERVICES
IN WIRELESS NETWORK ENVIRONMENT .......................................................................... 13
Abstract ......................................................................................................................................... 13
2.1. Introduction ............................................................................................................................ 14
2.1.1. Problem statement ............................................................................................................... 15
2.1.2. Challenges associated with quality of service .................................................................... 15
2.2. Methodologies........................................................................................................................ 16
2.2.1. Different QoS scheme for wireless network ....................................................................... 16
2.2.2. Fault Tolerant Dynamic Channel Allocation Scheme ........................................................ 16
2.2.2.1. Centralized approach ....................................................................................................... 16
2.2.2.2. Distributed approach ........................................................................................................ 16
2.2.3. Call Admission Control (CAC) Scheme ............................................................................. 17
2.2.4. Mobility Prediction Scheme ............................................................................................... 19
2.2.5. Dynamic Allocation Scheme using Renegotiation ............................................................. 21
2.3. Discussion and Conclusion .................................................................................................... 22
2.3.1. Results Discussion .............................................................................................................. 22
2.3.2 Conclusion ........................................................................................................................... 23
2.3.4. Future work ......................................................................................................................... 24
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CHAPTER THREE: CHAPTER THREE: ANALYSIS OF QUALITY OF SERVICE FOR
WCDMA NETWORK IN MWANZA, TANZANIA .................................................................. 25
Abstract ......................................................................................................................................... 25
3.1. Introduction ............................................................................................................................ 25
3.1.1. Received Signal Code Power (RSCP) ................................................................................ 26
3.1.2. Ration of Received Power to Noise (𝑬𝒄/𝑵𝒐) .................................................................... 27
3.1.3. Speech Quality Index (SQI) ............................................................................................... 27
3.1.4. Transmitting Power (TX power) ........................................................................................ 27
3.2. Methodologies........................................................................................................................ 28
3.2.1 Feasibility Study .................................................................................................................. 28
3.2.2. Drive Test............................................................................................................................ 28
3.3. Results and Discussion .......................................................................................................... 28
3.3.1. Coverage in terms of RSCP ................................................................................................ 29
3.3.2 Coverage in terms of EC/No ................................................................................................ 30
3.3.3. Transmission Power ............................................................................................................ 32
3.3.4. Call Information Overview ................................................................................................. 34
3.3.5. Low Received signal level .................................................................................................. 34
3.3.6. Lack of Dominant Server .................................................................................................... 35
3.3.7. Sudden appearance and disappearance of neighbour .......................................................... 35
3.3.8. Drop Call due to Bad Coverage: ......................................................................................... 35
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3.4. Recommendation ................................................................................................................... 35
3.5. Conclusion ............................................................................................................................. 36
CHAPTER FOUR: PLANNING AND OPTIMIZATION OF 3G NETWORK WITH
PERFORMANCE COMPARISON BETWEEN THE OPERATORS OF MOBILE
COMMUNICATION SERVICES ................................................................................................ 37
Abstract ......................................................................................................................................... 37
4.1. Introduction ............................................................................................................................ 38
4.2. Radio network Planning Process ........................................................................................... 39
4.2.1. Radio Link Budget (RLB) .................................................................................................. 40
4.2.1.1. Interference margin: ......................................................................................................... 41
4.2.1.2. Fast fading margin (= power control headroom): ............................................................ 41
4.2.1.3. Soft handover gain, as was discussed by (Laiho, 2002): ................................................. 41
4.2.2. Downlink Load Factor ........................................................................................................ 46
4.3. Capacity and Coverage Planning ........................................................................................... 48
4.3.1. Iterative Capacity and Coverage Prediction ....................................................................... 48
4.3.2. Detailed Coverage Planning ............................................................................................... 50
4.3.3. Detailed Capacity Analysis ................................................................................................. 50
4.4. Results and Discussion .......................................................................................................... 51
4.4.1. Results for planning ............................................................................................................ 51
4.4.2. Network Optimization ........................................................................................................ 60
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4.4.2.1. Received Signal Code Power (RSCP) ............................................................................. 62
4.4.2.2. Received Signal Strength Indicator (RSSI) ..................................................................... 62
4.4.2.3. Ration of Received Power to Noise (EC/N0) ................................................................... 63
4.5. Performance comparison for all network operators ............................................................... 64
4.5.1. WCDMA Benchmarking Objectives .................................................................................. 64
4.5.2. Number of 3G sites ............................................................................................................. 65
4.5.3. Coverage Statistics .............................................................................................................. 66
4.5.4. Accessibility Statistics ........................................................................................................ 66
4.5.5. Retainability Statistics ........................................................................................................ 67
4.5.6. Soft Handover Statistics ...................................................................................................... 68
4.5.7. Coverage RSCP .................................................................................................................. 69
4.5.8. Quality EC/No .................................................................................................................... 70
4.5.9. Summary of all Comparison ............................................................................................... 70
4.6. Conclusion ............................................................................................................................. 71
CHAPTER FIVE: GENERAL DISCUSSION AND CONCLUSION ...................................... 73
5.1. General Discussion ................................................................................................................ 73
5.1.1. 2G network analysis ............................................................................................................ 75
5.1.2. 3G network analysis ............................................................................................................ 77
5.1.3 Environment, Planning and Optimization............................................................................ 80
5.2. Conclusion ............................................................................................................................. 82
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5.3. General Recommendations .................................................................................................... 85
REFERENCES ............................................................................................................................. 87
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LIST OF TABLES
Table 1.1: Summary description of research specific objective and the methodology used. ....... 12
Table 3.1: Mean, Mode, Median, Variance, Standard deviation and maximum and minimum
ranges of both RSCP and Ec/N0 in active set count ..................................................................... 32
Table 4.1: Parameters used in Uplink load factor calculations as described in (Laiho, 2002) ..... 45
Table 4.2: As was argued by (Laiho, 2002) and (Holma et al., 2010), Parameters used in the
downlink load factor calculation. .................................................................................................. 47
Table 4.3: Benchmarking Objectives ............................................................................................ 64
Table 4.4 Summary Comparison of voice, data, coverage and QoS ............................................ 70
Table 5.1 KPI’s for 2G network performance comparison. .......................................................... 75
Table 5.2: Data statistics comparison for 2G network operators ................................................. 76
Table 5.3: Summary of 3G analysis on voice, coverage and quality ............................................ 77
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LIST OF FIGURES
Figure 1.1: Trend of Mobile and Fixed line subscription in Tanzania as for report from TCRA .. 4
Figure 1.2: Voice telecom subscription for each operator up to June 2014 by the courtesy of
TCRA .............................................................................................................................................. 4
Figure 2.1: Distribution channel allocation model (source: http://en.kioskea.net) ....................... 17
Figure 2.2: Call Admission Control Algorithm (Kovvuri) ........................................................... 19
Figure 3.1: Coverage KPIs _RSCP_Long Call Mode .................................................................. 29
Figure 3.2: RSCP in active set count ............................................................................................ 31
Figure 3.3: Transmission Power from the base stations ............................................................... 32
Figure 3.4: Coverage summary of the whole sample region ........................................................ 33
Figure 3.5: Quality of Service summary of the entire sample region ........................................... 33
Figure 3.6: Summary of the call information overview ................................................................ 34
Figure 4.1: WCDMA radio network planning process ................................................................. 39
Figure 4.2: UpLink Iteration Process ............................................................................................ 42
Figure 4.3. Downlink iteration Process........................................................................................ 43
Figure 4.4: Area of interest which needs to be covered ................................................................ 52
Figure 4.5: Depiction of environmental terrain from our area of interest .................................... 53
Figure 4.6: Geographical environmental features of the area of interest, side view .................... 54
Figure 4.7: Geographical environmental pattern for consideration while planning ..................... 55
Figure 4.8:Timing Advance distribution....................................................................................... 57
Figure 4.9:RX Quality for downlink channel ............................................................................... 58
Figure 4.10: RX level Uplink channel .......................................................................................... 58
Figure 4.11: RX level downlink channel ...................................................................................... 59
Figure 4.12: Design layout of the BTS position ........................................................................... 60
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Figure 4.13: CPICH RSSCP ......................................................................................................... 62
Figure 4.14: CPICH RSSI ............................................................................................................. 63
Figure 4.15: CPICH Ec/N0 ........................................................................................................... 64
Figure 4.16: Site comparison for all operators in Mwanza region up to June 2014 ..................... 65
Figure 4.17: Coverage statistics of all 3G operators ..................................................................... 66
Figure 4.18: Accessibility of 3G sites ........................................................................................... 67
Figure 4.19: Retainability Statistics .............................................................................................. 68
Figure 4.20: Soft Handover statistics ............................................................................................ 68
Figure 4.21: Coverage RSCP Statistics ........................................................................................ 69
Figure 4.22: Quality Ec/No statistics ............................................................................................ 70
Figure 5.1: Geographical view of Mwanza and its salient features .............................................. 73
Figure 5.2: Mwanza view of the local residence settlement ......................................................... 74
Figure 5.3: Data Technology distribution ..................................................................................... 78
Figure 5.4: Modulation Schemes used .......................................................................................... 79
xvii
LIST OF ABBREVIATIONS AND SYMBOLS
3G- 3rd Generation
BER – Bit Error Rate
BS- Base Station
BTS- Base Transceiver Station
CAC- Call Admission Control
CBR – Call Blocking Rate
CDMA – Code Division Multiple Access
CDR – Call Dropping Rate
CST – Call Setup Time
DL – Downlink
Ec/No – Ration of Received Power per Noise Density
FACH – Forward Access Channel
FDMA – Frequency Division Multiple Access
FTP- Forced Termination Probability
GGSN – Gateway GPRS Serving Node
GPRS – General Packet Radio Service
GPS - Global Positioning System
GPS – Global Positioning System
HLR- Home Location Register
HO – Handover
HSDPA – High Speed Downlink Packet Access
HSPA – High Speed Packet Access
HSR – Handover Successful Rate
ITU – International Telecommunication Union
KPI – Key Performance Indicator
LFG- Limited Fractional Guard Channel
MAC- Medium Access Control
MH- Mobile Host
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MMM- Mobility Management Module
MS- Mobile Station
MSC- Mobile Switching Centre
MSS- Mobile Service Station
MT - Mobile Terminal
QAM – Quadrature Amplitude Modulation
QoS- Quality of Service
QPSK – Quadrature Phase Shift Keying
RF – Radio Frequency
RLB – Radio Link Budget
RNC- Radio Network Controller
RSCP – Received Signal Code Power
RSSI – Received Signal Strength Indicator
RX Power – Received power
RXQUAL – Received Quality
SAP- Service Access Point
SCCR- Successful Call Completion Rate
SGSN – Serving GPRS Serving Node
SQI – Speech Quality Index
TA – Timing Advance
TDMA – Time Division Multiple Access
TDSCDMA– Time Division Synchronous CDMA
TE- Terminal Equipment
TX Power – Transmission power
UL – Uplink
UMTS – Universal Mobile Telecommunication System
WCDMA – Wideband CDMA
3
CHAPTER ONE: GENERAL INTRODUCTION
1.Introduction
The massive growth of mobile phone communications in the developing world has changed the
way we used to look on our daily life. Most countries in the developing world have abandoned
their old ways of communication through wired technology and now they have catapulted into
wireless technology through mobile phone communication. For most people in the world if not
all the prevalent means of communication is through mobile phones. Since the beginning of the
new millennium the use of it is averaged for every 100 occupants in Africa, Latin America,
Caribbean and Asia to have reached 100 to 400% in a short period of only five years. This is
explained in (Orbicom, 2007).
Mobile communication continues to grow diversely throughout the world. According to (Forlin
et al., 2008; Rashid and Elder, 2009), the speed of mobile phone penetration as a necessary
device is ascribed by the influence of liberalization of telecommunication sector itself has easy
to use application, basic knowledge in normal usage of phones and the ability to communicate by
any language including the native ones.
In Tanzania the telecommunication industry continues to shine and dominate the ICT Subsector
in the contribution of day to day life and the GDP of the country (TCRA 2006). The country's
population is about 45 million people (National Census 2012), almost 28 million people are
mobile phone subscribers in different companies, namely Vodacom Tanzania, Airtel, Tigo,
Zantel, TTCL and Benson (Statistics of June 2014 TCRA).
4
Figure 1.1: Trend of Mobile and Fixed line subscription in Tanzania as for report from TCRA
Figure 1.2: Voice telecom subscription for each operator up to June 2014 by the courtesy of
TCRA
Many Tanzanians lives in the villages since the backbone of the economy is agriculture.
Coverage of the telecommunication networks in most of the rural areas in the country is very
poor. One reason being the scattered settlement of the indigenous, so it makes it difficult for
service providers to install many base stations as in urban areas. The cost of installation,
operation (most of the time by power generator since the power supply is not reliable) and
maintenance in rural areas provide a very small profit margin or a loss to the company most of
the time.
5
According to (Tacchi et al., 2003) Mobile phones capability to communicate is not limited
tphone'sser space, volume, medium or time, and therefore it makes the continuation of
communicative ecologies.
The main challenge when planning and designing the telecommunication network is
approximating the actual amount of cells needed to provide sufficient coverage in the area of
interest with capacity constraint. When we refer to coverage of the cell it means the actual area
covered by the Base Transceiver Station (BTS) and for the capacity of the cell it means the real
number of subscribers which can be supported by the BTS.
1.1. Background Information
According to (Sood, 2006), there is enough proof of the new mobile users to be rural area's
settlers, while according to ITU report in 2006 it shows Africa has the world fastest mobile
subscription in the world. Tanzania is currently estimated to be the fourth country in the
continent for mobile subscription with South Africa, Nigeria and Kenya are leading respectively
(ITU Report 2012).
As telecommunication markets mature and continue to diversify, in Africa mobile phones are
now mostly used as service delivery platforms instead of just a simple communication tool. In
2007 Connect Africa Summit, the President of Rwanda, said; “In 10 short years, what was once
an object of luxury and privilege, the mobile phone, has become a basic necessity in Africa”.
Also, due to (The Economist, 2008), “A device that was a yuppie toy not so long ago has now
become a potent force for economic development in the world’s poorest countries.”
The growth of mobile phone usage has simply reduced communication and coordination
expenses and it is now changing lives through the state-of-the-art applications and services.
Samuel et al. (2005) assessed the socioeconomic impacts of mobile communications on
6
households, rural communities and small businesses in South Africa, Tanzania and Egypt and
found out mobile phones helps to cut down the travelling necessity, supporting employment seek
out, increasing awareness of business information, and easy the communication into our inner
circle.
1.2. Research problem and justification of study
1.2.1. Research Problem
The scattered settlement and population in rural areas makes it difficult for proper planning of
radio frequency coverage. The installation of new base station in most of these areas is of low
profit margin to the network operators since most of the places lack permanent electricity, hence
needs to be operated by power generator, this calls for a proper design for better maximization of
performance throughput and capacity of the network.
1.2.2. Research Justification
Mobile phone usage is of much help in the development of rural settlers as it was depicted in the
study of “Contribution of mobile phones to rural livelihoods and poverty reduction in Morogoro
region, Tanzania.” The Study reports on the crucial role of mobile phones in lessening the
hardships of life as well as refining rural livings through the use of social networking, boost
people’s capability of dealing with an urgent situation, reduces travel expenses, capitalize on the
result of required trips, amplify secular user friendliness, and increase effectiveness of doing
things. Mobile phone lowers business expenditures and escalate production by supporting rural
traders and farmers to find suitable market and prices (Sife et al., 2010).
Coverage and capacity can be improved through the addition of new cells into a network. But
addition of new sites goes with hefty additional costs to network operators which most of the
7
time are not ready to incur. This calls for a proper research on finding new ways and technique to
augment coverage by lowering the costs.
According to the (GSMA- 2011) report it is anticipated that by 2015 there will be a large number
of people owning mobile phones in the sub-Saharan Africa than electricity in their homes as the
use of mobile phone services will surpass the provision of other primary infrastructure therefore
communication industry will have larger significance into social life and society. Apart from
making communication more meaningful and easier, it will expedite sectors like education,
banking, agriculture, health care and women empowerment to be delivered with simplicity to the
society.
1.3. Objectives
The objectives of this research were laid down as follows;
1.3.1. General objective
The main objective of this research is to study network coverage of different wireless
technologies used by telecommunications vendors in rural areas and to give suggestions for
improving them.
1.3.2. Specific objectives
i. To analyse the quality of service (QoS) of the mobile network operators in rural areas
ii. To identify the geographic terrain pattern of the area needed for the selected telecom site.
iii. To plan and optimize for best radio coverage of the specific area
1.4. Hypotheses/Research questions
i. What is the quality of mobile network services in rural areas of Tanzania?
ii. What is the geographical terrain profile needed for better planning?
8
iii. How can a radio coverage be planned to achieve better optimization of the Base Transceiver
Station (BTS)?
The main goal of the RF planning is to achieve greater coverage and capacity with the resource
at hand while preserving a great deal of quality of service. Planning undeveloped network for the
purpose of serving a certain number of subscribers is not the major challenge to discuss, but the
main issue is to carry a real network planning which will allow the forthcoming expansion in
case there is a need so as to help trimming down the cost for the operator while continuing to
provide good service.
According to (Tutschku et al., 1996), planning means projecting the way the network it’s going
to serve the customers. This is done by describing the actual number of cell sites needed and
their location to be placed, the kind of configuration needs to be done for the system to run and
lastly the types of hardware and software needed. All these should be detailed by experienced
and knowledgeable radio frequency engineers.
The principle activity in planning process decides on the amount of cell sites from all the
possible sites that have been evaluated to cover the targeted market. As for (Hurley, 2002), the
chosen cell sites should meet the predefined criteria of the network operator normally to have
good coverage area with maximum capacity that cost less. In order for the criteria to work, the
necessity of defining suitable configuration parameter comes into effect.
The World today witness the massive use of advance technology in both mobile communication
and internet. The new advance technology offers a different quality of service to each user
depending on their location and the predefined network capacity. (Kajackas et al., 2011),
urgues that, it causes the unsettled quality of arguese to individual subscribers and the QoS of
the individual customer can not be generalized.
9
As planning seems to be a complex process (Tutschku et al., 1996), discuss the novel idea of
analytical planning. This approach gives attention to the ability of the radio engineers to
handpick the suitable places for cell sites and to designate frequency on the new sites by
inspecting the radio wave propagation and the nature of the environment with regards to
interference among adjacent cells. The method considers the inclusion of subscriber’s behaviour
and Tele Traffic in later stages of the planning process.
The study of radio propagation in rural residential areas with vegetation by (Blaunstein et al.,
2003) reveals that, the trees have both absorbing effects (instigated by scattering from foliage)
and diffraction effect ( which is due to lateral wave produced by the top l(er of the tree) which
affect the radio wave propagation at large.
(Dawy et al., 2003) defines the coverage of the cell as the geographical area which reach out to
the limit of Base Station (BS), and the capacity of the cell is described as the amount of Mobile
stations (MS) that can be served by the BS.
In defining coverage, it is indicated that due to the very rapid transition from near perfect to no
reception at all, it is necessary that the minimum required signal level is achieved at a high
percentage of locations. For mobile reception the percentages defined to be 99% for good and
90% for acceptable (ITU Report, 2012). Due to the high costs and the scarcity of radio resources,
an accurate and efficient mobile network planning procedure is required. The objective of
network planning is to maximize the coverage, capacity and the quality of service (Guo et al.,
2003).
10
1.6. Research methodology
1.6.1. Analysis of Quality of Service (QoS)
This study aims to collect opinions from subscribed customers of telecommunication operators
on how satisfied they are with the services provided in rural areas, Also the customers will state
what they are expecting to get in their areas from most network operators, or what they think
these operators should do and currently they are not doing, in terms of customer services, signal
reception and transmission i.e. Making and receiving a call, services like text messages and data
for those interested in data services. The study also is expected to evaluate the strength of signals
from different base stations in Lake Victoria Zone (Mwanza, Geita, Shinyaga, Mara and Kagera
regions). The Lake, Victoria Zone is depicted as a case study due to its complexity in its
geographical terrain pattern (i.e., the presence of the Lake Victoria itself and also the rocks
surrounding the area). The geographical feature hinders the propagation of signal at large extent
and also the electromagnetic waves tend to behave differently where transferred across the lake
zone. This calls for a proper research in the area to maximize the coverage despite of all the
challenges of the area.
A drive test is going to be conducted from selected rural areas of the mentioned regions. Data of
signal strength will be taken starting from a distance of 100 meters to at least 6 kilometres on
each side of the directional antenna allocated to the particular base station. The process will be
repeated for each sector of the base station for the entire coverage zone of the base station. This
process will be facilitated by the use of TEMS Investigation tools. Whereby the TEMS mobile
phone will collect these data and send them to TEMS log file where they will be manipulated to
analyse the quality of services from those areas.
11
1.6.2. Site Selection
The study also is expected to cover the range of processes involved in the selection of the
particular areas to mount a base station, knowing the longitude, latitude and altitude required
through proper surveys will be used to identify the modes of propagation which the area is
suitable for. Propagation in the land mobile service at frequencies from 300 to 1800MHz is
affected in varying degrees by topography, Morphography, ground constants and atmospheric
conditions. Upon getting a clear clarification of all the effects which will be present in the areas,
a single site will be depicted from among the several candidate sites. This process will involve
the use of software like MapInfo and tools like GPS at large extent.
1.6.3. Planning and Optimization
The next phase will be to plan for Radio Frequency (RF) coverage and optimization. Network
planning can be explained as devising the system which will enable customers to communicate
within the limit such system. The planning process is detailed into few steps as follows;
• Network dimensioning involves;
o Defining network requirements
o Defining the network configuration
o Projecting coverage area
o Projecting capacity of the channel
• Network planning and implementation which deals with;
o Coverage planning and Site selection which gives;
Defining number of sites and site acquisition.
Defining propagation models based on geographical, environmental nature.
12
o Capacity requirement which deals with;
Traffic and service distribution
o Parameter planning
Network optimization
The planning process always starts from the subscriber’s point of view, the need to cater for the
new emerging market or to easy traffic on the overloaded site. The customer’s views give an
insight what kind of network to be planned and integrated into the core network.
After the planning process being incorporated as full-fledged running network, then comes the
work of conforming the predefined criteria on QoS to whether they are met.
Table 1.1: Summary description of research specific objective and the methodology used.
S.no. Objective Methodology
1 To analyse the quality of service (QoS)
of the mobile network operator in rural
areas
Feasibility Study.
Drive test, measured by using TEMS
Automatic tools, devices and software.
2 To identify the geographic terrain
pattern of the area needed for the
selected telecom site.
Feasibility Study
MapInfo software
GPS
Google Earth
3 To plan and optimize for best radio
coverage of the specific area
MapInfo Software
TEMS Automatic
Asset
Google Earth
13
CHAPTER TWO: 1REVIEW OF SCHEMES FOR ANALYZING QUALITYOF SERVICES IN
WIRELESS NETWORK ENVIRONMENT Adolph kasegenya1, Anael Sam2
Abstract
Resource allocation and management is the fundamental key in providing better service using
mobile communication systems. This paper reviews the schemes for providing Quality of
Service (QoS) in the mobile wireless network environment. The paper will evaluate a total of
four schemes; this includes Fault Tolerant Dynamic Allocation Scheme, which deals with the
methods of reusing the channels effectively between two adjacent cells to avoid co-channel
interference. The second is a Call Admission Control Scheme, which deals with pre-blocking of
calls based on the available bandwidth for handling calls. Third scheme is Mobility Prediction
Scheme, which collects the information of the mobile host while travelling in a vehicle and store
the information into a database. And lastly Dynamic Allocation using Renegotiation Scheme
where the bandwidth usage changes dynamically depending on its availability. These schemes
are used in different environments to increase the quality of services of mobile communication.
Each scheme has its strong and weak point, depending on the parameters they are to analyse.
Key words: Quality of Service (QoS), Resource allocation, voice and data services, wireless
network.
1A. T. Kasegenya, Dr. A. Sam, “Review of Schemes for Analyzing Quality of Service in Wireless Network
Environment”, Conference Proceedings of the Pan African Conference on Science, Computing and
Telecommunications (PACT 2014), July 14 -18, 2014, Arusha – Tanzania.
14
2.1. Introduction
Quality of Service (QoS) in cellular networks is defined as the capability of the cellular service
providers to provide a satisfactory service which includes voice quality, signal strength, low call
blocking and dropping probability, high data rates for multimedia and data applications etc. For
network based services QoS depends on the following factors;
Throughput: The rate at which the packets go through the network. The maximum rate is
always preferred.
Delay: This is the time which a packet takes to travel from one end to the other.
Minimum delay is always preferred.
Packet Loss Rate: The rate at which a packet is lost. This should also be as minimum as
possible.
Packet Error Rate: These are the errors which are present in a packet due to corrupted
bits. This should be as minimum as possible
Reliability: The ability of the network to carry it’s functionality as desired or per
specification.
If infinite network resources were available, then all application traffic could be carried at the
required bandwidth, with zero latency, zero jitter and zero loss. However, network resources are
not infinite. As a result, there are parts of the network in which resources are unable to meet
demand. QoS mechanisms work by controlling the allocation of network resources to application
traffic in a manner that meets the application's service requirements. [7]
15
2.1.1. Problem statement
Imagine the scenario where you are talking with your friend and you suddenly experience a call
drop or maybe you can’t hear properly with what your friend is talking due to signal scrambling.
It is highly undesirable and you do not want to be in a network of such kind while you’re paying
for the desired service. To realize the conducive environment for communication in wireless
network, effective QoS schemes are needed. Scheme and issues related to better QoS is the main
subject of this paper.
2.1.2. Challenges associated with quality of service
The main challenges when considering the issue of QoS in mobile phone network environment
are issues like bandwidth allocation, varying rates, channel characteristics, fault tolerance level
and handoff support in heterogeneous wireless networks. Each layer of the OSI architecture has
its mechanism to provide a better QoS so as to attain network flexibility and tolerance. One of
the biggest challenges in the cellular network in today’s world is the proper and efficient usage
of the spectrum. Bandwidth allocation plays a vital role in this aspect. While designing we
should take into account the issue of bandwidth allocation by imploring schemes like
Renegotiation scheme for allocating the bandwidth to lower priority class just to make sure
everything is utilized to its fullest. The issue of QoS gets much more complicated when we deal
with the QoS of both voice and data at the same time and in the same network. Voice services
are very delay sensitive and require real time service while on the other hand, data services are
less sensitive to delay, but very sensitive to loss of data that is why there is a need of error free
packets all the time. All issues of bandwidth, latency, jitter and loss need to be considered for a
proper designing in order to obtain a better quality of service of the network. [6 – 7], [9], [15].
16
2.2. Methodologies
2.2.1. Different QoS scheme for wireless network
There are so many QoS schemes deployed to be used in cellular network depending on the
application it’s going to serve. Some of these schemes are such as Fault Tolerant Dynamic
Allocation scheme, Call Admission Control (CAC), Mobility prediction scheme, and
Renegotiation Scheme.. [1 – 5].
2.2.2. Fault Tolerant Dynamic Channel Allocation Scheme
2.2.2.1. Centralized approach
In this approach the mobile station (MS) sends a request to the central controller, which is called
Mobile Switching Centre (MSC). The MSC is the only component which is responsible for
channel allocation and distribution of all resources to avoid co- channel interference between
cells. When the MSC encounters a problem and fails, then the entire network of that MSC it also
fails to operate. This approach is not scalable because the MSC can become a bottleneck when
the traffic load of the system is heavy.
2.2.2.2. Distributed approach
This approach does not depend on MSC as the centralized one rather the nearby base station
share the responsibility to allocate channels through the use of Mobile Service Station (MSS).
The base stations are independent to communicate with each other by using the MSS component
and to share information. The base station that wants to borrow a channel it will send the request
to all the nearby base stations through the communication of the MSS and when the reply come
that there is a free channel in any one of the nearby channels then it uses that channel. This is
done in collaboration with all nearby channels by sharing the information thus to avoid the co-
17
channel interference which might occur. This approach is scalable, reliable and robust and thus it
guarantees the QoS of the cellular network. [1],[6],[19 – 24].
Figure 2.1: Distribution channel allocation model (source: http://en.kioskea.net)
2.2.3. Call Admission Control (CAC) Scheme
In the CAC algorithm scheme the new call arriving will be processed by comparing the
estimated rate of call arriving with the predetermined rate of call arriving. If the estimated rate is
higher compared to the predetermined level then the fraction of calls will be blocked regardless
of the availability of the channels in the cells. The main objective of this scheme is to avoid the
bottleneck of the incoming traffic. The QoS on this scheme is achieved through the use of
parameters like Forced Termination Probability (FTP), which is defined as the ration of the
number of calls which are forced to terminate due to failed handoff to the number of calls that
successfully entered the network. Another parameter is the Successful Call Completion Rate
18
(SCCR), which is defined as the number of calls which are completed successfully in a unit time
by each cell. [2],[25 – 28]
When the new call arrives the algorithm check whether the acceptable load is less compared to
the estimated load. If the answer is less then it check for the availability of a free channel in the
cell otherwise if the estimated load is greater than the acceptable load, then the algorithm will
calculate the fractional amount of calls which will be allowed and the remaining fraction which
is exceeded will be discarded even if there are available channels. This is called pre-blocking of
channels and through this the scheme improves the FTP and SCCR of the profiled users. [2],[30]
19
Figure 2.2: Call Admission Control Algorithm (Kovvuri)
2.2.4. Mobility Prediction Scheme
The Mobility Prediction Scheme is used to determine the path of the trajectory of a mobile node
and this path information is stored in the database from time to time. Normally there are channels
reserved for handoff process, so this scheme, there is prioritization of resources before handoff
occur so as to decrease the call probability rate at the handoff. Through this the handoff can be
predicted earlier and the resources will be reserved for the same. [3],[25 – 28],[30].
20
While travelling in the vehicles the mobile host (MH) will encounter a number of handoff when
communicating. By studying the information about the road topology and to store them in the
database from time to time, then the prediction algorithm will prove to be suitable. The figure
above shows a number of base stations when the MH is moving in a vehicle. This database of the
base station, it records information’s such as average time to transit a segment, neighbouring
segments at each junction and the probability of the MH to do a handoff. Every time the base
station is able to collect the information of the moving node, then it will update its database to
prepare resource incase this node will require a handoff in the near future while communicating.
Through this the management of handoff is done precisely by reducing the probability of call
block and forced termination due to lack of resource, hence improved QoS of the entire system
[3], [28 – 30]
21
Figure 2.1: Topology information for Mobility Prediction Scheme (Soh)
2.2.5. Dynamic Allocation Scheme using Renegotiation
In this scheme when the medium level is free of using its resources, then the low level priority is
given those resources. This scheme increases the QoS of the over whole network system by
making sure the high priority they are served effectively while also the low priority doesn’t
execute for a long time.
22
With the massive development of mobile phone technology now the world is trying to find its
feet in 4G technology, therefore the battle for resources between conversational and streaming
classes is becoming intense. With services like video telephony, Telnet, voice and video we
expect the network to employ real time traffic data which are delay sensitive while the
application like emails, news, FTP and all kinds of surfing over the web browser are less delay
sensitive. [10 – 13]
In Renegotiation scheme the conversational classes are assigned with maximum priority say
class 1. While the streaming classes are also given high priority say class 2. But the priority class
1 and 2 when arrived at the first time will be served if there are enough resources to
accommodate them, if not they won’t be admitted. But lower priority class, let’s assume class 3
which has interactive services like chart messages and emails will be admitted at any time they
knock in since they require lesser bandwidth compared to class 1 and 2. The big advantage of
these schemes is when bandwidth is allocated to high class priority it can be transferred when
that particular task is completed. Also lower priority class they can use more resources than they
previously asked if the resources are available. And at this time when the higher priority class
arrives, it won’t be blocked even if there are no enough resources, but rather it will take those
resources allocated to low class from the high class and reuse them. [4 – 6],[16],[18]
2.3. Discussion and Conclusion
2.3.1. Results Discussion
The Dynamic channel allocation Scheme is fault tolerant since it gives us an opportunity to reuse
the channels. Also, since it doesn’t use the MSC as the centre of its operation as the cell
communicate with each other then we have seen there is no need to get the response from all the
23
adjacent cells for borrowing a channel. Therefore, this scheme, it helps to reduce the overall
congestion in the network.
The CAC scheme utilizes the combination of the pre-request scheme and guard channel scheme
to avoid the bottleneck of the incoming calls, hence it helps to reduce the number of blocking
calls.
The Mobility Prediction Scheme it uses the information it collects from the mobile host when
travelling and prepare the resources for handoff when needed. This helps to avoid unnecessary
call drops during the handoff procedure.
The Renegotiation Scheme it makes sure the QoS of highest priority is not disturbed while
allocating the unused resources to the low priority. Through this the overall QoS of the network
is improved through idle resource distribution even though they didn’t ask for that amount of
resource
2.3.2 Conclusion
Quality of service as an essential tool in wireless network communication depends on the choice
of the scheme for a certain application. We have seen scheme like Fault Tolerant Dynamic
Allocation reduces the overall network traffic congestion. And Call Admission Control balances
the network load by blocking the incoming calls even if there were available channels. While the
Mobility Prediction Scheme uses the information it collects in advance to set the room for
handoff to occur without causing dropped calls. Lastly the Renegotiation Scheme, which
guarantees the QoS of low priority by reallocating the unused resource. These schemes are
essential tools in analysing the quality of service the network can provide to its users.
24
2.3.4. Future work
In the near future the drive test, measurement will be conducted in Mwanza region to collect data
about Network Fault related parameters such as Fault Incidence rate, Mean Time to repair,
Network availability (coverage) also Network reliability with parameters like Call set-up success
rate (within own network), Service Access Delay, Signal strength and voice quality, Call Drop
rate percentage of connections with good voice quality and data quality. This data will help me
to examine these schemes of QoS into details.
Acknowledgement
I sincerely thank the Almighty God for giving me the will and courage to complete this work.
Then my supervisor Dr. Anael Sam for working hand with hand to the completion of this work.
25
CHAPTER THREE: CHAPTER THREE: 2ANALYSIS OF QUALITY OF SERVICE FOR
WCDMA NETWORK IN MWANZA, TANZANIA
Adolph kasegenya1, Anael Sam2
Abstract
This paper presents an analysis and evaluation of a WCDMA network in both rural and urban
areas of Mwanza, Tanzania. The analysis of data starts by collecting data through a drive test,
measurement by using TEMS Investigation tool. The parameters which are analysed in this
paper are such are Received Signal Code Power (RSCP), Transmitted Power (TX), Speech
Quality Index (SQI) and the ration of received power to noise (Ec/N0). The data collected
shows that only 24.02% of the region has got the best coverage, 23.24% has poor coverage and
the 52.74% has a fair coverage. Also by using the basic Key Performance Indicators (KPI’s) we
analysed the data for the quality of service (QoS) of the area which shows only 27.61% of the
region has good QoS, while the poor value recorded with 2.76% of the region. We can use the
analysis done in this work to stage and support system optimization for telecom service
providers so as to improve their performance of services in this area.
Keywords: WCDMA, Received Signal Code Power, Coverage and Quality of Service
3.1. Introduction
Quality of Services in mobile environment can be defined as the proficiency of mobile operators
to deliver acceptable services to mobile subscribers as for the predefined key performance
2International Journal of Information Engineering and Application (IJIEA). Volume 4 Issue 10, October, 2014,
ISSN: 2225 - 0506; Accepted and ready for publication by Adolph Kasegenya and Anael Sam from the school of
Computational Communication Sciences and Engineering (NMAIST).
26
indicators set. The services delivered include good voice services with low blocking and
dropping probability, good signal strength with high data rates.
Tremendous growth of the mobile phone market in Africa and the introduction of smart phone
for communication have changed the way we used to look for cellular network services. There is
an increase demand for converged services supporting multimedia such as video and audio in
mobile communication systems. Provisioning of quality of service (QoS) in converged networks
is becoming much more complex.
The main challenges when considering the issue of QoS in mobile phone environment are issues
like bandwidth allocation, varying rates, channel characteristics, fault tolerance level and handoff
support in heterogeneous wireless networks. Each layer of the Open System Interconnection
(OSI) model has its own mechanism to provide better QoS so as to attain interoperability,
various standards, network flexibility and tolerance. One of the biggest challenges in the mobile
phone network in today’s world is the proper and efficient usage of the spectrum resource such
as frequencies, scrambling codes, spreading factors, power for common and dedicated channels
Bandwidth allocation plays a vital role in this aspect. There is a great challenge when the issue of
data and its application is evaluated for better QoS of the mobile network. Supporting both data
and voice application needs a better understanding of how they work. Voice need real time
operation since they are delay sensitive. While on the other side data are sensitive to loss of data.
The following parameters were the keys of this analysis;
3.1.1. Received Signal Code Power (RSCP)
The “Received Signal Code Power” (RSCP) means the power measured by the receiver on a
physical communication channel. This power denotes the strength of the signal measured, the
27
condition for handover to occur, how to find path loss and moreover it’s a power control in
downlink channel.
3.1.2. Ration of Received Power to Noise (𝑬𝒄/𝑵𝒐)
𝐸𝑐𝑁𝑜Account for all received energy per chip from the Node B when divided by the power
spectral density in the given band of operation. ‘No’ contains the actual power of a particular cell
from the designated total received power. Hence 𝐸𝑐/𝑁𝑜 is decreasing the value for ‘No’
increase. It is expressed into 𝑑𝐵.
EC/No for a UE is the measure of PCPICH (code power) over Total Wide Band Power on that
particular carrier. Measure of PCPICH (RSCP) 𝑑𝐵𝑚 and measure of Total Wideband power
(RSSI) 𝑑𝐵𝑚. So the𝐸𝑐/𝑁𝑜 will become;
EC/No = RSCP / RSSI (1)
(By applying logarithmic rule) into (1) then we get
Ec/No = RSCP – RSSI (dB) (2)
3.1.3. Speech Quality Index (SQI)
SQI is a performance metric for voice quality in telecommunication. It is specific only to the
TEMS family of drive testing/field testing tools. SQI aims to provide a reasonable estimate of
the voice quality, as perceived by a human ear.
3.1.4. Transmitting Power (TX power)
The kind of power which carries the signal from Node B (BTS) and transmitting it to User
Equipment (UE) or mobile communication device. TX power needs to be sufficient enough to
ensure the reliable communication between the Node B and UE.
28
3.2. Methodologies
3.2.1 Feasibility Study
While conducting analysis of QoS in Mwanza, a keen feasibility study was conducted to gather
information about; system parameters of equipment which have been installed in Mwanza,
including the transmission capacity for sites, class of services offered and network configuration
in terms of data rates, Number of sites, prospective customers and criteria for addition of sites,
Frequency Band (Uplink and Downlink), Modulation schemes, and factors which degrades
Quality of Service.
3.2.2. Drive Test
The analysis of QoS in Mwanza region was done through Drive Test, measurement where the
tester collected log files through the TEMS investigation tool and analyses them through Actix
Analyzer and Map Info. The main objectives of this DT were to check the coverage of the area,
accessibility, handover success rate and retain-ability of the cellular network in general.
3.3. Results and Discussion
The following graphs were obtained after the log files collected from the drive test was simulated
and analysed in Actix Analyzer and Map Info software.
29
3.3.1. Coverage in terms of RSCP
Figure 3.1: Coverage KPIs _RSCP_Long Call Mode
30
3.3.2 Coverage in terms of EC/No
Figure 3.1: Coverage KPIs _CPICH Ec/No
31
Below is the summary of the above findings from the maps
Figure 3.2: RSCP in active set count
Figure 3.1: The 𝐸𝑐/𝑁0 in active set count
0%
5%
10%
15%
20%
25%
30%
35%
40%
0
2000
4000
6000
8000
10000
12000
< -130.0 -130.0 to-115.0
-115.0 to-100.0
-100.0 to-90.0
-90.0 to -80.0
-80.0 to -70.0
-70.0 to -60.0
-60.0 to20.0
> 20.0
% S
am
ple
s
Sam
ple
Co
un
t
RSCP (dBm)
Strongest RSCP in Active Set
0%
10%
20%
30%
40%
50%
60%
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
< -20.0 -20.0 to -17.0
-17.0 to -15.0
-15.0 to -13.0
-13.0 to -11.0
-11.0 to -9.0
-9.0 to -5.0
-5.0 to0.0
% S
am
ple
s
Sam
ple
Co
un
t
EcIo (dB)
Strongest EcNo in Active Set
32
Table 3.1: Mean, Mode, Median, Variance, Standard deviation and maximum and minimum
ranges of both RSCP and Ec/N0 in active set count
Statistic Strongest EcNo in AS Strongest RSCP in AS
Mean -9.3 -87.4
Mode -9.0 -89.0
Median -9.0 -87.0
Maximum -2.5 -50.0
Minimum -24.0 -121.0
Count 31792 31792
Standard Deviation 2.7 12.7
Variance 7.1 161.9
3.3.3. Transmission Power
Figure 3.3: Transmission Power from the base stations
33
Coverage summary
Figure 3.4: Coverage summary of the whole sample region
The results show the best coverage in the entire sample of evaluation was only 24.02%, while the
poor coverage below the minimum value was 23.24% of the whole region. This shows the rest of
the region has a fair coverage, which is not enough for the good quality of service of the whole
region.
Quality of Service Summary
Figure 3.5: Quality of Service summary of the entire sample region
24.02
52.74
23.24
Coverage
Good RSCP > -80 dBm Fair -80 to -95 Poor below -95 dBm
27.61
69.62
2.76
Quality
Good Ec/No > -8 dB Fair -8 to -15 Poor below -15 dB
34
The overall QoS which is greater than -8dB was only 27.61% and the poor quality of service
which is below the -15dB was 2.76%. The results show most of the region is under fair quality of
service of about 69.62%.
3.3.4. Call Information Overview
Figure 3.6: Summary of the call information overview
Bad quality of service of the entire region shows the rate of call drop was above 60%, while the
rate of the overall call success rate was below 40%.
Now from the above graphs we can say that;
3.3.5. Low Received signal level
Most of the places of this region are covered by different types of terrain, structures like hills,
mountains and tall rocks which results in loss of line of sight to the transmitted signal. In places
where the signal received level is below the threshold, then there are coverage holes and those
places can be seen with the red colour on the above two maps. Attenuation of signal due to high
mountains, hills and valleys contributes much to downlink low level signal strength. Also the
low number of serving sites and path loss due the effect of Rayleigh Fading was another reason
35
for reduced signal strength. Poor coverage due to the low received signal level results into bad
quality of service and hence call drops.
3.3.6. Lack of Dominant Server
Due to the low value of CPICH power, the MS was experiencing a high number of handover.
This was because the MS was located at the border of the cell and there was no BTS with strong
signal to support and keeping the call. It keeps on receiving signals from more than one cell,
hence results in interference and handover.
3.3.7. Sudden appearance and disappearance of neighbour
Due to different terrain changes and obstacles from tall rocks the neighbour cells were popping
up with high levels of signal, hence resulting into a lot of handover over a short period of time to
the BSC. The effect is famously known as “The ping pong effect”.
3.3.8. Drop Call due to Bad Coverage:
The signal level goes down beyond the minimum RX Access level to which prevents the on-
going call to drop. This is mostly due to bad coverage as it is shown on both coverage maps of
RSCP and CPCIH.
3.4. Recommendation
The best solution in most of the coverage problems will be installations of new base station. But
due to budget limits and operations under low profit margins in most of this area, it is difficult to
be implemented.
Therefore, it is better to do site auditing to check for corrects antenna orientations, antenna tilts
and antenna type as for specific environments. Also to check the possible attenuation of the cells
through faulty feeders, jumpers, connectors and other faulty equipment.
36
To increase strong received signal it is better to deal with unnecessary down tilts, proper
investigation of the existence of natural diversity like forest hills, tall rocks and valleys as well as
to increase the height of the site. Putting high gain antennas and increasing output power could
improve the coverage.
3.5. Conclusion
The coverage of this region is bad in most of the places due to poor RSCP as it is shown in the
above analysis of the map extracted from the log files. The transmitting power also degrades as
the User Equipment moves away from the BTS. All of this and other factors which have been
discussed above results into call drops, muted calls and fluctuation on coverage for both data and
voice. Even though the quality of service is not that much bad, but there are many problems due
to coverage and they need to be taken care as soon as possible. Proper optimization is needed to
be done in most of the area to increase the quality of service in the region. New sites can be
added to complement the problems of coverage, especially in areas where they lack dominant
server.
37
CHAPTER FOUR: 3PLANNING AND OPTIMIZATION OF 3G NETWORK WITH
PERFORMANCE COMPARISON BETWEEN THE OPERATORS OF MOBILE
COMMUNICATION SERVICES
Adolph kasegenya1, Anael Sam2
Abstract
This paper presents WCDMA radio network planning. The Planning process involves network
dimensioning, thorough capacity planning and coverage planning as well as network
optimisation. The WCDMA network dimensioning comprises of the information’s of base
stations and their design criterion and other network elements as for the operator’s preferences
and the radio propagation of the selected area. The dimensioning of the network needs to achieve
the operator’s prerequisites intended for coverage of the cell, traffic capacity and the basic
Quality of Service (QoS) projected. These two aspects are attentively correlated in WCDMA
networks, consequently all of them need to be reflected concurrently in the process of network
dimensioning. With the help of network planning tools like Asset software, Google Earth, Map
Info and Tems Investigation kit both channel capacity planning and coverage planning of the cell
are assessed simultaneously for WCDMA networks. With detailed planning, the actual
propagation plots and operator’s traffic assessments in respective areas are of crucial importance.
After the planning process being commissioned, then the network implementation comes into
effect, and here the network operation and its performance were observed through network
performance tests, and the outcomes of these tests were used as the foundation stage for network
optimisation. Also the comparison of performance of services between all the operators in terms
of voice services, data services and its application, coverage through Received Signal Code
3International Journal of Technology Enhancements and Emerging Engineering Research (IJTEEE). Volume 2
Issue 11, November, 2014, ISSN (Online): 2347 - 4289; Accepted for publication by Adolph Kasegenya and Anael
Sam from the school of Computational Communication Sciences and Engineering (NMAIST).
38
Power (RSCP) and Quality of Service through the ration of Received Power to Noise (EC/No)
was conducted for all operators.
4.1. Introduction
The Third Generation networks which are based on Code Division Multiple Access (CDMA) is
also referred as Universal Mobile Telecommunication System (UMTS) is categorized into three
standards as per International Telecommunication Union (ITU) specification, these standards are
such as Wideband CDMA (WCDMA), CDMA2000, and Time Division Synchronous CDMA
(TDSCDMA). CDMA is a digital mobile communication technology that employs spread-
spectrum methods. It doesn’t allocate frequency explicit to individual subscriber, but it ensures
each channel exploit the disposal of efficient usage of complete spectrum. Distinctive colloquies
are encrypted with a pseudo-random digital system (Eisenblatter et al., 2008)and (Guo et al.,
2003).
As was elaborated by (Toskala et al., 2001), the first commercial 3G network was launched in
Japan in 2001, while in Europe was launched in 2003 in parts of the Uk and Italy. The
commercial launch in Africa took place in 2006 by EMTEL Company in Mauritius. The spread
of WCDMA networks in most countries was hindered by the huge superfluous cost of licensing
spectrum fees. Since WCDMA operates with different frequency range when compared to GSM,
then network vendors in many countries were required to build their networks with new
specification which conforms to new frequencies of UMTS. The licence fees for the new
frequencies in these countries were predominantly high due to the limited number of frequency
sold by most governments and also early agitation of 3G’s prospective. Other holdups were due
to the overhead of setting up a new network.
39
The main components of 3G network include BS (Base Station) or node B, RNC (Radio
Network Controller), together with Wideband CDMA Mobile Switching Centre (WMSC) and
the Serving GPRS Support Node (SGSN) /Gateway GPRS Support Node (GGSN). WCDMA
network aid vendors to operate with the maximum spectral efficiency with better management of
traffic capacity and a variety of improved sophisticated services. These services are such as
video calls, broadband wireless data and voice telephony in a conducive and efficiently manner.
Additional features such as High Speed Packet Access (HSPA), it has ability of transmitting data
with speed up to 14.4Mbps on the downlink and 5.8 Mbps in the uplink.
4.2. Radio network Planning Process
WCDMA radio network Planning process as it was described by (Laiho et al., 2006). The below
graph depicts the necessary footsteps for WCDMA planning methods.
Figure 4.1: WCDMA radio network planning process
40
System dimensioning is a key task in network planning. It provides an early assessment into
network environment count as well as the supplementary channel capacity components. These
components are such as radio network and the core network. Due to time constraints, this paper
will deal with the radio network section exclusively.
The initial stage of planning requires the planner to evaluate the special features like the
population density of the area, morphographic features (environmental area types), topographic
features (terrain heights), natural vegetation and network configuration parameters and sub
parameters of the area. This stage consists of the activity like Radio Link Budget (RLB) were the
uplink and downlink power are estimated, coverage prediction were the area to be covered is
plotted with all the salient features required, capacity prediction were the ability of BTS is
compared to the traffic density of the area, and lastly the number of required BTS to handler all
the traffic in accordance with the estimated population density of the area, Radio Network
Controller (RNC), equipment for different interfaces and the core network elements needed.
Network dimensioning outlays how the traffic will be distributed in the network, the future
expected traffic growth and the basic QoS needed. This stage also introduces the Call Admission
Control (CAC) algorithms for managing the blocking probability.
4.2.1. Radio Link Budget (RLB)
The RLB in UMTS networks, is a little more complex, as every user is generating interference to
others in the same network. (Laiho et al., 2006) describes that, the RLB takes into account the
existence of parameters like antenna gains, cable losses, diversity gains, fading margins and
handovers while dimensioning the radio network. The RLB computation yields to maximum
tolerable propagation path loss, which is deemed to determine cell range and the highest number
of cell sites required. Thus the cell radius is reliant on the traffic capacity at any absolute time,
41
and the outcome of this has to be projected on a series of repeated methods for uplink and
downlink evaluation. Both uplink and downlink estimation will yield in a cell range value which
the final value will be the lower of the two iterations on average.
The following parameters are the additional from the link budget equation of the TDMA-GSM
based.
4.2.1.1. Interference margin:
The importance of the interference margin in this link budget is clearly depicted by (Mahato,
2007), due to the presence of features like loading of the cell and the load factor in effect of
coverage analysis. The more loading capacity is sanctioned in the system, the larger is the
interference margin needed in the uplink, and the smaller is the coverage area. In coverage
limited cases, a smaller interference margin is used while in capacity limited cases we used a
larger interference margin. Also (Glisic, 2003), explains coverage limited cases whereby the cell
size is limited by the maximum allowed path loss in the link budget, while the maximum air
interface capacity of the base station is not used. The typical values for the interference margin in
coverage limited cases are 1.0 to 3.0dB, which corresponds to 20 to 50% loading.
4.2.1.2. Fast fading margin (= power control headroom):
For keeping up sufficient closed loop fast power control, the headroom is needed in the mobile
station transmission power. This is especially for slow moving pedestrian mobiles where fast
power control is able to compensate the fast fading. The typical value for the fast fading margin
are 2.0 to 5.0dB for slow moving mobiles.
4.2.1.3. Soft handover gain, as was discussed by (Laiho, 2002):
The soft handover gives a gain contrary to slow fading by diminishing needed log-normal fading
margin. This is due to the reason that the slow fading is partly uncorrelated between the base
42
stations and by making handover the mobile can select a better base station for its operations.
This gain provides extra macro diversity gain contrary to fast fading by decreasing the needed
Eb/N0 in relation to a particular radio link. The extent of gain can be expressed in terms of
mobile phase, the types of algorithms deployed into the receiver and supplementary gains which
are presented into the received signal. The absolute soft handover gains it’s in the range of 2.0
and 3.0 dB. The following graph depicts the Uplink iteration process for RLB calculation as was
discussed by (Laiho et al., 2006)
Figure 4.2: UpLink Iteration Process
Connect MSs to best server, calculate needed
MS TX Power and SHO gains
Check UL loading and possibly move MSs to
new other carrier of outage
Calculate adjusted MS TX powers, check MSs
for outage Calculate new i = ioth / lown
Set old Threshold to the default/ new coverage
threshold
Calculate new coverage threshold
Check hard blocking and possibly take links
out if too few HW resources
Evaluate UL break criterion
Initialisation
End
Post Processing
DL Iteration step
Convergence
No
n
Co
nv
er
ge
nc
e
43
The Downlink iteration process takes into consideration the total downlink power as its reference
point and not the level of interference in the system as its counterpart Uplink iteration process it
considers. The keen descriptive data for both the process are not shown for the sake of brevity of
the concerning company. The graph of the downlink iteration process was explained by (Laiho et
al., 2006)
Figure 4.3. Downlink iteration Process
Initialise
Iterations
Calculate target C/I’s
Calculate Initial TX Powers
for all links
Determine the SHO
connections
Calculate the MS
Sensitivities
Calculate the received perch
levels and determine the best
server in DL
Allocate the CPICH powers
Global Initialisation
Initialise deltaCloid
Calculate the SHO
diversity combining gains;
adjust the required change
to C/I
Check CPICH Ec/Io
Calculate the C/I for each
connection
Calculate C/I for each MS
UL iteration setup
Check UL and DL break
criteria
Fulfil
led
End
Post Processing
Update deltaCloid
Adjust TX powers of
each remaining link
accordingly to deltaCl
44
The cell range value is calculated by using equation (3) as was depicted by (Hurtado, October
2005), were the minimum required power level at the receiver(sensitivity) is defined for a
reference user i of each service k.
RXlevel_i [dBm] = NF + 10 log (No) + 10 log (i_oi ) + 10 log [Eb/(No_k )] + 10log (R_k)
(3)
Where
• NF = Node B noise Figure [dB]
• No = thermal noise density, normally assumed to be -174 dBm/Hz
• Eb/No k = Eb/No for the service k
• Rk: Service k bit rate (bps)
• ioi = Noise Rise due to interference
To calculate the Maximum path loss, equation (4) is used
Lmax, i = PULk – Required_Leveli – Σ losses – Σ margins + Σ gains (4)
Where:
PULk is the mobile power valid for service k [dBm]. In this equation, all the losses, margins and
gains are given in dB.
After getting the maximum path loss (Lmax), then we apply a propagation model like Okumura-
Hata to determine the corresponding cell range. Then we are supposed to calculate the ability of
the cell to carry traffic so as to get the interference over noise rise and to make a comparison
with the figure at the end of the uplink iteration process.
Traffic per cell can be computed for each service, since the number of subscribers per square
kilometre is renowned from preceding processes of network dimensioning and the area of the
45
cell is conveyed from the cell range found previously. For example, for the standard hexagonal
cell with the type of antenna which radiates equally in all directions, then the area is
approximated to be 2.6R2, where R is the cell range in Kilometres.
By using modified Stochastic Knapsack model as was depicted by (Kumar et al., 2010) and
(Hodge, 2006), the capacity of cell can be computed by using equation (5);
η_UL (Uplink load factor) = (the number of active users) /(pole capacity) (5)
Where “Pole Capacity” means 100 % cell load and is given by equation (6);
𝑁𝑝𝑜𝑙𝑒 ,𝑈𝐿 = 𝑤/(1 + 𝑓𝑢𝑙) ∑ 𝑗 = 1 … 𝑘 𝑉𝑗 ∗ 𝑅𝑗 ∗ 𝑃𝑗 [𝐸𝑏/𝑁0 𝑗/(1 +𝐸𝑏
𝑁0𝑗
∗𝑅𝑗
𝑊)]
(6)
Where:
• W : chip rate, in W-CDMA is fixed to 3.84 Mchips/sec
• K = number of offered services
• Eb/No j is the required Eb/No for the service j (j=1… k)
• Rj is the bit rate of service j
• vj is the activity factor of the service j.
• Pj is the percentage of the total active users who are using service j
• 𝑓𝑢𝑙 = other cell / own cell interference ratio,
As they are received from Node B, For the ideal antenna which radiates equally in all sides, then
this value is approximated to be 55% (0.55).
Table 4.1: Parameters used in Uplink load factor calculations as described in (Laiho, 2002)
Definitions Recommended Values
N Number of users per cell
Activity factor of user j at physical layer
0.67 for speech, assumed 50% voice
activity and DPCCH overhead during
46
DTX
1.0 for data
Eb/N0 Signal energy per bit divided by the
noise spectral density that is required to
meet a predefined Quality of Service
(e.g. Bit error rate). Noise includes both
thermal noise and interference
Dependent on service, bit rate,
multipath fading channel, mobile
speed, etc.
W WCDMA chip rate
3.84 Mcps
Rj Bit rate of user j Dependent on service
i Other cell to own cell interference ratio
seen by the base station receiver
Macro cell with omnidirectional
antennas: 55%
Lastly after having the cell load, then we need to calculate the Interference Noise rise as it is
given by equation (7);
𝑁𝑅 [𝑑𝐵] = − 10 𝐿𝑜𝑔10 (1 − 𝜂𝑢𝑙) (7)
Then we need to approximate the conjunction of the resultant value with the presumed one in the
preliminary stage. The computation of Radio Link Budget (RLB) and the analysis of coverage
gives out the cell range value and its subsequent cell area coverage
4.2.2. Downlink Load Factor
As was described in (Holma et al., 2010), the downlink load factor η, Can be explained on the
ground of comparable analysis as the uplink factor even though they are considerably unlike.
The downlink factor can be calculated by using equation (8);
𝜂𝐷𝐿 = ∑ 𝜐𝑗 .(
𝐸𝑏𝑁0
)𝑗
𝑊/𝑅𝑗
𝑁𝑗=1 . [(1 − 𝛼𝑗) + 𝑖𝑗] (8)
Where−10 ⋅ 𝑙𝑜𝑔10(1 − 𝜂𝐷𝐿) is equal to the noise rise over thermal noise due to multiple access
47
Interference. As explained by (Laiho, 2002), the new parameter 𝛼𝑗 , Symbolize the orthogonality
factor in the downlink channel. The WCDMA employs orthogonal codes to distinct subscribers,
despite being deprived of any multipath propagation the orthogonality persists the signal is
received by the UE. By any chance when the delay is of large extent, then, the UE will receive
this signal as multiple access interference. The orthogonality of 1 corresponds to perfectly
orthogonal users (Toskala et al., 2001). The typical value of orthogonal ranges between 0.4 and
0.9 in multipath channel (Sipila et al., 1999).
Table 4.2: As was argued by (Laiho, 2002) and (Holma et al., 2010), Parameters used in the
downlink load factor calculation.
Definition Recommended values for dimensioning
N Number of connections per cell =
number of users per cell x (1 + soft
handover overhead)
Activity factor at physical layer 0.67 for speech, assumed 50% voice
activity and DPCCH overhead during
DTX
1.0 for data
Eb/N0
Signal energy per bit divided by noise
spectral density, required to meet a
predefined Quality of Service (e.g. Bit
error rate). Noise includes both thermal
noise and interference
Dependent on service, bit rate,
multipath fading channel, mobile speed,
etc.
W WCDMA chip rate
3.84 Mcps
Rj Bit rate of user j Dependent on service
αj Orthogonality of user j
Dependent on the multipath propagation
1: fully orthogonal 1-path channel
0: no orthogonality
ij Ratio of other cell to own cell base
station
Each user sees a different ij, depending on
its location in the cell and log-normal
48
power, received by user j
shadowing
Average orthogonality factor in the cell ITU Vehicular A channel: ~60%
ITU Pedestrian A channel: ~90%
The average ratio of other cell to own
cell base station power received by the
user. Own cell interference is here
wideband
Macro cell with omnidirectional
antennas: 55%
4.3. Capacity and Coverage Planning
4.3.1. Iterative Capacity and Coverage Prediction
The network dimensioning phase enabled us to obtain the cell count, which now will be used in
network planning by taking into account the radio frequency and its associated favourable
environmental conditions with digital maps of high resolution, which shows all necessary
geographical data and precise propagation models, to simplify to exercise of estimating the
optimum number of base station required.
In order to come up with a meticulous channel capacity and coverage planning, as explained by
(Laiho, 2002), the actual propagation information from the selected site are indispensable
collectively with the anticipated user density and projected traffic load. Meanwhile the
knowledge of the surrounding Node B’s is highly required with their performance data so as to
evaluate the option of reusing the existing cell sites in the area. The outcome of these two
processes of planning for capacity and coverage are such as the exact location to install a Node B
as well as the necessary constraints required.
Since users in WCDMA share the similar resources in the air interface for the interference, then
these users they cannot be analysed independently. The influence between each user interference
49
causes their transmission power to change. As a result the whole extrapolation process becomes
iteratively until the transmission power is steady. The multipath channel profiles, bit rates and
mobile speeds play a vital role in both capacity and coverage planning. Also the WCDMA, it
includes features like fast power control in both uplink and downlink, soft and softer handover
and orthogonal downlink channels to enhance its performance. Other things to note in coverage
and capacity planning in WCDMA are, things like interference estimation which is crucial in
coverage prediction phase, also the base station sensitivity depend on the number of users and
used bit rates in all cells.
In WCDMA, coverage and capacity need to be analysed concurrently due to the fact that they are
both influencing each other and they result in phenomena like cell breathing where the cell
coverage area shrinks (i.e., mobile phones which are transmitting at their maximum power in the
cell border cannot increase their power levels more and eventually they get disconnected unless
the handover takes place with the help of the nearby cell) if there is higher interference in the
cells (intra-cell/ inter-cell interference).
The tangible specified planning stage on WCDMA network it looks similar to TDMA/FDMA
planning in GSM network. The BTS or Node B spot and their region segments are deployed in
planning software were the significance of the transport layer is evaluated. The mobile station
densities in different cells are based on the actual traffic information. The hotspots should be
identified as an input for accurate analysis.
In 3G networks the prerequisite number of cells to cover a particular area can be calculated based
on the capacity and the radio link budget. The network usually acts as either coverage limited
(i.e., there is an adequate amount of capacity resources in the cell to sustain the traffic forecasted,
even though the maximum cell range of a mobile transmission power limits it) or capacity
50
limited (i.e., the maximum cell radius cannot support the total traffic offered because of
insufficient resources). [ITU]
4.3.2. Detailed Coverage Planning
Once we have the geographic data, clutter information and accurate propagation models, then the
coverage planning starts so as to identify the number of base stations and their locations by using
proper planning tools like Asset software. Also the advanced features are evaluated to avoid
undesirable phenomena like pilot pollution (where the presence of too many pilots with
maximum power levels in the same area, cause interference and higher error rates as a receiver
are designed to handle the maximum of only 4 pilots) and Ping-Pong effect which causes the
excessive handovers and increased dropped call rates.
Thus the coverage planning includes the following activities;
Channel power planning (to avoid pilot pollution)
Detailed characterization of the radio environment
Soft handover parameter planning
Iterative network coverage analysis based on the simulation tools and
Network optimization to ensure efficient usage of network resources
4.3.3. Detailed Capacity Analysis
While planning the 3G network in capacity aspect we should note that it is very important to
ensure that the current resource meet the current traffic demand for a greater quality of service
(capacity management) without forgetting to plan for the future load dimensioning (capacity
planning). One of the reason for planning these two factors coverage and capacity
simultaneously is that the detection of capacity complications in the network is unconventional
in WCDMA, since the load system depends on several parameters like traffic load of individual
51
service (data influx route), user mobility profile, spatial distribution of traffic demand, the
geographical environment (urban, suburban and rural) and other physical radio parameters like
efficiency of Rake receivers and macro diversity gains. According to (Hurtado, October
2005),the capacity planning need to adhere to the following fundamental issues;
To guarantee that the presented resources are used to deliver the uppermost performance
(capacity management)
In addition, there will be enough resources to encounter the upcoming workload
requirements (capacity planning).
Detailed capacity analysis is the process to ensure the above two fundamental issues are certain
while planning.
4.4. Results and Discussion
4.4.1. Results for planning
The output from network dimensioning gave us the clear picture of both capacity, coverage and
quality predictions. From capacity planning, we knew the spectrum available, the subscriber
growth forecast and the traffic density map. While in coverage planning, we determined the
coverage regions and the area, type of information associated with the regions we want to cover,
preferred antenna line system specifications, suitable propagation model, field strength
predictions and coverage threshold values on per regions (outdoor, in-car and indoor). Finally,
both capacity and coverage ensure we had better quality of service by having low blocking
probability and good threshold values on per regions coverage for most of the area.
Normally planning is done in two scenarios where it is either the capacity planning which
originates from technical department through customer complaints or coverage planning which
originates from the marketing department for expansion of the network.
52
Coverage planning is done where the area does not have a pre-existing site from the core
network and there is demand from the new market prediction. A polygon of the area is drawn to
show the dimensions of the area needed to be covered. Coverage prediction goes hand in hand
with the development of digital map where the information like topography (terrain heights) and
morphography (area types) are evaluated.
The capacity planning is done through optimizing the existing infrastructure by looking at ways
to ease traffic to the overloaded BTS. Capacity planning examines the capacity of each sector by
comparing its actual capacity and the estimated capacity. If the subscriber densities are much
greater compared to the entire capacity of the BTS then that is the call of adding new sites to
accommodate the traffic needed.
The following Nyarugusu area was planned for both coverage and capacity planning as the area
is illustrated in the given polygon below due to its potential new market.
Figure 4.4: Area of interest which needs to be covered
53
The blue colour shows the entire area which needs to covered by the new sites. Therefore the
first work was to define the features of the area through network dimensioning. The planning
gave out the details of how many BTS are needed to cover the whole area and where to place
those BTS with their sectors.
From the below digital map we can describe the topographical features (terrain heights) and
morphographical features (area types).
Figure 4.5: Depiction of environmental terrain from our area of interest
The digital map shows us that the area is not a smooth area, but it contains mountains and
valleys, as it can be seen by following the red line. Hence putting the BTS along this line, it’s too
risk as it may result in biased transmission of signal by covering one side and hindering the
signal in another side. The geographical terrain of this area from the line drawn shows it’s not
54
suitable for BTS installation and sectorization and hence we have to try to plot the coverage in
another direction.
Figure 4.6: Geographical environmental features of the area of interest, side view
From the above map it shows the line was drawn from the high mountain to the valley. At least
the terrain of this area gives us a hope of mounting a BTS as attitude from the sea level continue
to decrease as we go down the line. From the starting point, it’s a high mountain, but coming
down, it’s a valley up to the end of the polygon where the line ends.
The mere description of the area is as follows through the below figure;
Diffraction:
Point to point communication system (i.e., line of sight) is galvanized by the fundamental
principle of radio path consent in the middle of antennas. Moreover is the main determinant
components of propagation requirements of communication system. When a large object exists
in the signal path between two broadcasting antennas, it normally reduces the signal strength due
55
to the fact that the radio link depends on the amount of energy bent nearby the blocking target,
and not on direct line of sight.
Radio frequency signals in diffraction can propagate behind any hindering objects, even though
the received signal strength will be promptly reduced as a receiver is moving closer into the
hindered object (shadowed) region. In this area of interest of which we planned for the new BTS,
the diffraction occurs due to the presence of big rocks, mountains and valleys.
Figure 4.7: Geographical environmental pattern for consideration while planning
Reflection:
Reflection takes place when the angle of incidence is equal to the angle of reflection in a
conducting surface. Loss of signal in reflection is caused by either absorption or direct passing of
light into a conducting material or medium. In long distance communications, wet areas, sea and
lakes are the best reflectors while the desert and landfall areas are poor reflectors. While in short
range communication the good reflectors are buildings and any other metallic structures. The
56
presence of forest trees and other natural vegetation were of great concerns when planning for
better coverage in our area of interest.
Refraction:
The Snell’s Law states that 𝑛1 𝑠𝑖𝑛𝜃1 = 𝑛2 sin 𝜃2 Whereby we know if 𝑛1 has got the refractive
index, which differs to 𝑛2, then when electromagnetic waves move between these two media it
will change the direction as it cross from media with refractive index one to refractive index 2.
When it comes to a radio frequency signal, the direction of signal will abruptly bend rather than
undergoing a quick change in direction.
Scattering:
Scattering happens when the radio frequency signal hits a rough surface (within homogeneities)
and as a result the signal get dispersed instead of being absorbed. The resulting signal is less
significant than the original signal. Scattering of RF signals in this region occur much when they
encounter things like rocky terrain, leafy trees, chain link fencing rain as well as dust.
Absorption:
Absorption occurs when the Radio Frequency signal is transformed into heat. The RF waves
move faster than the molecules of the media where the RF is passing and causes absorption to
occur. In this area where the planning was done the absorption occur since the area is rich in
water and there are wood forest.
After examining the environment into details and its nature description, then it follows the design
process of how the antennas will be placed. Here we look at the antenna orientation, antenna
heights, antenna tilt and the antenna types.
57
The following graphs show the detailed planning for power estimation and the quality of power
received
Figure 4.8:Timing Advance distribution
From the figure above, we know Timing advance (TA) value corresponds to the length of time
a signal takes to reach the base station from a mobile phone. The TA value used was between 0
and 63, with each step representing an advance of one bit period (approximately 3.69
microseconds).
RX Quality
58
Figure 4.9:RX Quality for downlink channel
Rx Quality this is the other name for Bit Error Rate (BER), so BER defines the Rx quality. It
means that the lower the percentage of the BER, the better the Rx quality. The extents of full and
sub samples are contingent on the speech activity elements which is renowned as DTX factor.
The variance in the BER averaging methods, results into considerable dissimilarities in the
RXQUAL distributions.
UL RX level
Figure 4.10: RX level Uplink channel
59
From the figure above the BTS was set with the operating range of power from -50dBm up to
less than -100dBm. But the signal was more efficient in the range of -70dBm to -95dBm.
DL RX level
Figure 4.11: RX level downlink channel
The figure above shows the range of downlink RX power which goes to the UE from the Node B
or BTS was from -50dBm to -100dBm. But for convenient communication link the UE needs to
receive the power in the range of -60dBm to -95dBm.
60
Figure 4.12: Design layout of the BTS position
The figure above shows the coverage of our sample area. Where the entire given area was
successfully covered as for the description of colours. The BTS were placed at a distance of 6km
from each other and we had a total of 3 BTS for the whole area to be covered.
4.4.2. Network Optimization
When the network is already in place and its running, then comes the work of checking if the
predictions made were correctly and the basic KPI’s for quality analysis as for the operator’s
rxlev>=-75
Good
-95<=rxlev<-75 Fair
rxlev<-95 Bad
Legend
61
settings were met. Here we look at how network resources are shared and distributed as for the
services offered. The key performance indicator for the operational network were evaluated by
using network status analysis tools like Measurement Reading Report (MRR), and the radio
resource parameters were tuned for best performance. Based on definite data, the ability of the
new defined network will be assessed on its adeptness to predict the traffic load.
Optimisation needs to be evaluated based on the KPI’s defined in early stage. The field measured
data were compared to the measurement from network management system data and the
comparison were used to describe the quality of service of the new network. The performance of
radio resource management algorithms (i.e., handovers, power control, admission and load
control and packet scheduling) were analysed by using the KPI’s results.
For the WCDMA networks, optimisation can be done automatically instead of being done
manually as for second generation GSM networks.
The following graphs are the results of optimisation done
62
4.4.2.1. Received Signal Code Power (RSCP)
Figure 4.13: CPICH RSSCP
The figure above shows the graph of Received Signal Code Power (RSCP) as the measure of
CPICH, with the standard deviation of 12.6, mean of -81.0 and a median of -82.0 for the total
active set count of 7101.
4.4.2.2. Received Signal Strength Indicator (RSSI)
The figure above shows the Received Signal Strength Indicator (RSSI). This is a value that takes
into account both RSCP and Ec/I0. RSSI is usually given in dBm and can be calculated as
through an equation;
RSSI[dBm] = 𝑅𝑆𝐶𝑃[𝑑𝐵𝑚] − 𝐸𝑐/𝐼𝑜[𝑑𝐵] (9)
The RSSI records the mean of -60.81, Median of -61.05 and the Standard deviation of 5.18
63
Figure 4.14: CPICH RSSI
4.4.2.3. Ration of Received Power to Noise (EC/N0)
The below graph shows the ration of Received Power to Noise (Ec/N0). EC/No for a UE is the
measure of PCPICH (code power) over Total Wide Band Power on that particular carrier.
Measure of PCPICH = RSCP dBm and measure of Total Wideband power = RSSI dBm
EC/No will become 𝐸𝑐/𝑁𝑜 = 𝑅𝑆𝐶𝑃 / 𝑅𝑆𝑆𝐼
𝐸𝑐/𝑁𝑜 = 𝑅𝑆𝐶𝑃 – 𝑅𝑆𝑆𝐼 (𝑑𝐵) (By applying logarithmic rule)
The graph shows the Mean of -10.04, the Median of -10.00 and the Standard deviation of 1.93.
64
Figure 4.15: CPICH Ec/N0
4.5. Performance comparison for all network operators
After the network was up and running, then comes the part of checking the performance of all
network operators in Mwanza region to see how they are providing their services.
4.5.1. WCDMA Benchmarking Objectives
Table 4.3: Benchmarking Objectives
Mode Objective
Idle -Compare Coverage
Dedicated mode
-Compare: Call Setup Time
-Compare: Accessibility
-Compare: Retainability
-Compare: Handover Success Rate
-Compare: Received Quality
65
The objective of this benchmarking was to compare coverage, call setup time, accessibility,
Retainability, handover success rate and received quality for Airtel, Vodacom and Tigo who are
currently the dominant operators in the region.
4.5.2. Number of 3G sites
The test covers the area of 425 square kilometres and it involves providing mobile
communication to at least 363,452 people. There are currently about 100 3G sites in the region,
and the distribution of sites for each operator are as in the graph below;
Figure 4.16: Site comparison for all operators in Mwanza region up to June 2014
66
4.5.3. Coverage Statistics
Figure 4.17: Coverage statistics of all 3G operators
From the figure above, it can be seen that Vodacom is the leading operator in this region when it
comes for good coverage, followed by Tigo which also had a remarkable coverage even though
they are short with a number of BTS when compared to Vodacom. And Airtel is lagging behind
in good coverage.
4.5.4. Accessibility Statistics
Operators
Total Call
Attempts
Total Call
Blocked
Accessibility-
CSSR%
Ranking
Airtel 97 18 81.44% 3
Vodacom 73 5 93.15% 2
Tigo 69 0 100.00% 1
67
Figure 4.18: Accessibility of 3G sites
The data show a good ratio of Call Setup Successful Rate (CSSR), for Tigo as they didn’t record
any call block. However, Vodacom they recorded 5 call drops for a total of 69 attempted calls,
while Airtel they had 18 calls blocked for a total of 97 attempted calls.
4.5.5. Retainability Statistics
Operators
Total Call
Established
Total Call Drop
Retainability-
DCR%
Ranking
Airtel 79 6 92.41% 2
Vodacom 68 0 100.00% 1
Tigo 69 0 100.00% 1
68
Figure 4.19: Retainability Statistics
From the figure it can be depicted that Vodacom and Tigo they have a good ratio of the Call
Completion rate for all their attempted calls 68 and 69 respectively. While Airtel had only 6
dropped calls out of 79 attempted.
4.5.6. Soft Handover Statistics
Operators Total HO OK Total HO Fail HO SR Ranking
Airtel 1746 0 100.00% 1
Vodacom 1701 0 100.00% 1
Tigo 1566 0 100.00% 1
Figure 4.20: Soft Handover statistics
In the case of soft handover, all operators had a perfect score without handover failure.
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4.5.7. Coverage RSCP
Figure 4.21: Coverage RSCP Statistics
Coverage in terms of Received signal Code Power (RSCP), was better for Vodacom as they
recorded an average of 81.2%, followed by Airtel for having 58.1% of good ratio of RSCP
received. While Tigo lag behind for recording only 57.4% of good signal received.
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4.5.8. Quality EC/No
Figure 4.22: Quality Ec/No statistics
The Quality of Service (QoS) in terms of ration of Received Power to Noise (EC/No) shows a
little prospect for Vodacom with a record of 43.9%. While Airtel and Tigo recorded 34.6% and
32.6% respectively. Both companies need to strengthen this area of QoS.
4.5.9. Summary of all Comparison
Table 4.4 Summary Comparison of voice, data, coverage and QoS
No. KPI Score Ranking
AIRTEL VODACOM TIGO AIRTEL VODACOM TIGO
1 Voice Score (%) 74.46% 89.92% 92.65% 3 2 1
2 Data Score (%) 87.10% 24.30% 27.60% 1 3 2
3
Coverage (% of
samples RSCP > -
82dbm)
58.10% 81.20% 57.40% 2 1 3
4 EcNo (% of
samples 0-8) 34.60% 43.90% 32.60% 2 1 3
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The above table summarises all comparison where it shows the strength and weakness of every
operator in the region so far. Were Tigo are leading in Voice services followed by Vodacom and
Airtel are the last. While in terms of data services and applications, Airtel is the leading operator
followed by Tigo and Vodacom are the last. In the case of Coverage through RSCP, Vodacom is
leading with its 47 Node B’s, and is followed by Airtel with its 26 Node B’s and Tigo are closing
the curtains with its 27 Node B’s. Lastly the case of QoS through the EC /No, again Vodacom is
leading, followed by Airtel and Tigo are in the last position.
4.6. Conclusion
The planning and optimisation process for the WCDMA was done successfully. In dimensioning
the network we looked into how the Radio link budget can be calculated, the range between
cells, which for better coverage, we decided for it to be 6km up to 9km apart for rural areas
where for urban area it is better to be situated to 1km distance. Also the capacity estimation by
looking onto the total number of sites required to cover the area given by comparing to the total
traffic density of the area. Lastly, we explore the suitability of the geographical environment for
positioning the Base Station. Lastly, we optimised the power through RSCP, RSSI, and EC/No
so as to obtain a better quality of service to places where there where the demand was not met.
After considering all necessary parameters while looking at the nature of environment the
coverage, capacity and quality of service of the given area were so much better. While at the start
of this research Tigo was last in comparison in every category, but after going through a proper
ways of planning and optimisation procedure, now they are the leading operators in terms of
Voice and they are also in second place when it comes to data services and its application.
Acknowledgment
72
My heartfelt gratitude to my Supervisor Dr. Anael Sam for being with me and guiding me
through the completion of this work without getting tired. Also to all Tigo staffs who participated
in one way or another in the completion of this work. From planning the network, analysing the
suitable environment, optimising the network and lastly is correcting data and do the keen
analysis of performance of all operators in the region. I have nothing to repay for your kindness
and support, but am praying to God, May you succeed in your endeavour.
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CHAPTER FIVE: GENERAL DISCUSSION AND CONCLUSION
5.1. General Discussion
Coverage problems are so wide in the interlacustrine region. The Lake, Victoria coast is famous
for its natural vegetation and the physical nature, bringing in complexity in mobile network
planning, designing and implementation. The presence of huge rocks gives Mwanza a famous
name of Rock city. Other geographical salient features of the area are like deep valleys, forest
trees, long rivers, hills and mountains covered by tall rocks. The native people of this area
reside in the wide valleys, slopes of the mountains and hills where they have built up houses and
make living in such environments.
Figure 5.1: Geographical view of Mwanza and its salient features
74
Figure 5.2: Mwanza view of the local residence settlement
This area has three giant network operators, namely Vodacom, Airtel and Tigo. Zantel is present,
but not so popular. These three operators cover the region with about 100 Node B’s for 3G
technology covering an area of 425 square kilometres and a population of 363,452. The
distribution of the Node B’s is 47, 26 and 27 for Vodacom, Airtel and Tigo respectively. They
both operate in the frequency of 2100 GHz for single carrier. In the case of GSM technology, the
BTS are 43 for Vodacom, 29 for Airtel and 24 for Tigo, which add to a total of 96. Therefore the
total number of BTS and Node B in the region is 196.
This research examines the QoS of the area on the basis of the basic KPI’s set by the Tanzania
Communication Regulatory Authority (TCRA), for both GSM technology (2G network) and
UMTS technology (3G network).
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5.1.1. 2G network analysis
The analysis indicates that Tigo is doing better in terms of coverage recorded an average of
96.6%, followed by Vodacom recording 95.8% and Airtel is lagging with only 92.7%. The
quality of the received signal (RXQUAL), Tigo has done a good job with 98% of good quality,
followed by Airtel with 95% and Vodacom is lagging with 88.7%%.
In the case of Call Setup Success Rate (CSSR), Tigo has 96.63%, Vodacom 93.41%, and Airtel
86.00%, for Call Drop Rate (CDR), Tigo has a drop rate of 3.49%, Airtel 4.65% and Vodacom
recorded a drop rate of 11.76%. Then for Call Blocking Rate (CBR), Tigo recorded a blocking
rate of 3.37%, Vodacom 6.59% and Airtel 14.00%. The analysis of the Call Setup Time (CST),
Airtel had the lowest CST of 2.4 Seconds, Tigo 2.5 Seconds, and Vodacom with 3.4 Seconds.
Lastly, we analysed Handover Success Rate (HSR), were Vodacom had no handover failure for
all the samples, Tigo had a failure of only 0.51%, which means it recorded HSR about 99.49%,
and Airtel 96.82 with a failure of 3.18%.
The analysis for Voice, coverage and Quality, the table below summarises the analysis
Table 5.1 KPI’s for 2G network performance comparison.
2G - Airtel
2G - Vodacom
2G - Tigo
KPI Mwanza KPI Mwanza KPI Mwanza
No. of Sites 29 No. of Sites 43 No. of Sites 24
Number of Blocked
calls 14
Number of Blocked
calls 6
Number of Blocked
calls 3
Number of Drop
calls 4
Number of Drop
calls 10
Number of Drop
calls 3
% of Rxlevel
sample better than -
75 dBm
92.70%
% of Rxlevel
sample better than -
75 dBm
95.80%
% of Rxlevel
sample better than -
75 dBm
96.60%
76
% of Rxlevel
sample between -75
dBm to -85 dBm
6.10%
% of Rxlevel
sample between -75
dBm to -85 dBm
3.90%
% of Rxlevel
sample between -75
dBm to -85 dBm
3.10%
% of Rxlevel
sample between -85
dBm to -95 dBm
1.10%
% of Rxlevel
sample between -85
dBm to -95 dBm
0.30%
% of Rxlevel
sample between -85
dBm to -95 dBm
0.30%
% of Rxlevel
sample below -95
dBm
0.10%
% of Rxlevel
sample below -95
dBm
0.00%
% of Rxlevel
sample below -95
dBm
0.00%
% of RX Qual
samples < 6 95%
% of RX Qual
samples < 6 88.70%
% of RX Qual
samples < 6 98.00%
The analysis of data and its application had a total of three KPI’s, analysed Radio Link Control
(RLC) throughput Downlink is greater than 60kbps were Tigo recorded 19.60%, Airtel 19.50%
and Vodacom had 10.20%. For Uplink Vodacom had 0.1%, while both Tigo and Airtel had 0%.
Another KPI was the File Transfer Protocol (FTP) Throughput where Airtel recorded 67.46%,
Tigo 43.92 percent and Vodacom had only 28.18%. The FTP Success Rate, Tigo had 15.38%,
Airtel 12.50 and Vodacom had 4.7%. Lastly, we analysed the Ratio of Carrier to Interference
(C/I) for the ratio which is greater than 9 and the statistics were as follows, Tigo had a ratio of
96.90%, Airtel 94.90% and Vodacom 80.40%.
Table 5.2: Data statistics comparison for 2G network operators
No. KPI Score Ranking
Airtel Vodacom Tigo Airtel Vodacom Tigo
1 RLC throughput DL >60
(kbps) 19.50% 10.20% 19.60% 2 3 1
2 RLC throughput UL > 60 0 0.1 0 2 1 3
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(kbps)
3 FTP Throughput 67.46 28.18 43.92 1 3 2
4 FTP Success Rate 12.50% 4.70% 15.38% 2 3 1
5 C/I Ratio > 9 94.90% 80.40% 96.90% 2 3 1
Recommendations as for above observation
These are general recommendation for the sake of brevity in individual operator.
In some places where cell did not give coverage as per desired direction the following
recommendation was given out;
o Site audit to check physical parameter and site configuration.
For the case of poor quality patch due to overshooting;
o Site audit for antenna orientation and also handover definition.
Overshooting cell which creates missing neighbours;
o Needs to check frequency planning and site neighbour planning.
Poor quality due to abnormal overlaid (OL)/under laid (UL) coverage distribution;
o Need to check the Site for OL/UL settings, which cause abnormal coverage
patterns.
5.1.2. 3G network analysis
Since the entire research analysed in details the 3G network. Here is the summary of all the
discussion.
Table 5.3: Summary of 3G analysis on voice, coverage and quality
3G - Airtel
3G – Vodacom
3G - Tigo
KPI Mwanza KPI Mwanza KPI Mwanza
No. of NodeB in
Town 26
No. of NodeB in
Town 47
No. of NodeB in
Town 27
Number of
Blocked calls 18
Number of
Blocked calls 5
Number of
Blocked calls 0
Number of Drop
calls 6
Number of Drop
calls 0
Number of Drop
calls 0
78
% of Rxlevel
sample better than
-75 dBm
38.1%
% of Rxlevel
sample better than
-75 dBm
56.4%
% of Rxlevel
sample better than
-75 dBm
38.7%
% of Rxlevel
sample between -
75 dBm to -85
dBm
29.8%
% of Rxlevel
sample between -
75 dBm to -85
dBm
31.1%
% of Rxlevel
sample between -
75 dBm to -85
dBm
30.1%
% of Rxlevel
sample between -
85 dBm to -95
dBm
18.7%
% of Rxlevel
sample between -
85 dBm to -95
dBm
10.4%
% of Rxlevel
sample between -
85 dBm to -95
dBm
25.4%
% of Rxlevel
sample below -95
dBm
13.4%
% of Rxlevel
sample below -95
dBm
2.1%
% of Rxlevel
sample below -95
dBm
5.8%
% of Ec/Io sample
better than -13 93.2%
% of Ec/Io sample
better than -13 92.1%
% of Ec/Io sample
better than -13 94.4%
Average App DL
Throughput -Kbps 1764.84
Average App DL
Throughput -Kbps 1194.16
Average App DL
Throughput -Kbps 1696.22
Figure 5.3: Data Technology distribution
79
Data technologies widely used are Forward Access Channel (FACH), High Speed Downlink
Packet Access (HSDPA), High Speed Packet Access (HSPA), HSPA Plus (HSPA+), PS DCH
R99 AND UMTS PS idle. All these technologies are used on the basis of environmental and
operator’s preferences. For example, Vodacom is good, mostly in HSPA+, UMTS PS idle and
FACH, while Tigo they strengthen themselves into FACH, HSPA, and UMTS PS idle. Airtel is
strong in HSPA+ and UMTS PS idle.
Figure 5.4: Modulation Schemes used
Both operators used mostly QPSK and 16QAM as their modulation schemes and introduction of
64QAM as the new technology. The world today in communication is more on multimedia than
voice communication. The operators need to adhere to this circumstance by increasing their
ability to accommodate more users while providing reliable data communication with high
downlink and uplink capacity.
Recommendations on 3G analysis
Poor RSCP coverage;
o Need to audit antenna orientation (azimuth).
o Antenna placement (electrical and mechanical tilt).
o Physical audit on hardware fault.
Poor quality
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o Call latched due to poor server; check the cell neighbour planning
o Pilot pollution in the region; physical site audit to change antenna electrical and
mechanical tilt.
The analysis of the QoS enables the evaluation of different schemes which are used to provide
better QoS in mobile communication environment, four schemes were evaluated based on their
strength and weakness. These schemes are as follows;
Fault Tolerant Dynamic channel Allocation Scheme
Call Admission Control Scheme
Mobility Prediction Scheme and
Dynamic Allocation Scheme using Renegotiation
And it was concluded that these schemes they do depend on each other for their functionality.
5.1.3 Environment, Planning and Optimization
The issue of coverage and capacity planning which goes concomitant with selecting the best
place for putting Node B, which is based on favourable geographical environment pattern.
Planning for coverage and capacity is done concurrently.
There is still a room for research on the case of environmental pattern which causes the mobile
phone signal to be degraded. One of the reasons identified in this research is the presence of
blackspot.
Blackspot is described as the geographic, environmental area where the signal of the mobile
phones is degraded but not because the mobile phone is far from the transmission tower. The
study shows both the act of the mobile phone being far from a cell tower and being at blackspot
area they resemble in features. The following are the special features associated with both
phenomena;
High intensity of power usage
Call drops
Interference from another call when you’re making yours.
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Signal scrambling
High call setup time
Slow connection for internet
High number of handover failure
These characteristics and many others describe the same scenario, whether is blackspot or being
far from transmission tower. Both courses can be evaluated on environmental terrain basis or
non-terrain basis. There are additional factors like antenna placement (electrical and mechanical
tilt) as well as antenna orientation.
The suitable place for a cell tower mounting should consider also the presence of atmospheric
and tropospheric effects of electromagnetic and radio signal, Presence of forest trees and natural
vegetation at large extent in one area could be a problem, also the costs of Lake and oceans are
not so friendly with radio signal. Features like mountainous rocks and deep valley cause
diffraction, scattering effects, reflection and refraction of radio signal.
For planning, efforts should be on network dimensioning and defining the network parameter
configuration. Enough time should be spent with skilled and experienced engineers for site
information collection, devising the proper approach on ways for coverage, capacity and quality
planning, designing and optimization.
Operators in this region offer a wide range of wireless technologies, which help to ease the life of
local citizens. Such services are like SimBanking, services like M-PESA, AIRTEL MONEY and
TIGO PESA prove to be very beneficial to normal citizens. Now it’s easy to send or receive
money from one user to another, banking transactions and with the introduction of the M-PAWA
and TIGO WEKEZA as the new ways of storing money for subscribers of Vodacom and Tigo
respectively.
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The use of mobile apps facilitated by the introduction of Android as the new operating systems
for mobile phone have revolutionized the way we use to think of mobile phones services and
applications. The wide spread of mobile phone technology has now reached into sectors like
education where the use m-learning facilitates education deliverance, in agriculture the use of
m-Agri good example is tigokilimo a new Tigo service for farmers to tap the opportunity to
expand their crop production, markets and healthcare services through mobile applications.
All these are needed by the rural settlers probably more that urban settlers, Since education is
well delivered in urban, more schools with better teachers than in rural areas, therefore there is a
need to enable the use of m-learning to deliver the same education in rural as in urban areas.
Hospital services are also not so good in rural areas while in town there are a number of hospitals
with good services. Now it’s time to use m-healthy to deliver such services.
5.2. Conclusion
Proper planning and designing is the key to coverage and performance improvement in the world
of telecommunication networks. The process of planning and designing telecommunication
network requires more experienced radio frequency engineers who are strongly equipped,
knowledgeable and skilled in defining networks at its initial stage. Network definition laid the
foundations for the network parameters and sub parameters required for configurations of the
new site, the type of hardware required for the new site and the relation between the new site and
the existing nearby sites. In network definition, it’s where the new site information was described
and the strategies of the whole planning were drawn. Understanding the geographical,
environmental pattern surrounding the area was another key feature for increasing coverage of
mobile phones especially in rural areas. The geographical pattern had significant impact on how
the radio frequency is transmitted and received. The degradation of the efficiency of the
83
communication links where possible and to the large extent contributed by neglecting thorough
investigation of the importance of geographical environmental pattern in the planning process.
The propagation models were defined based on the nature of the environment of the new site.
The number of sites was defined based on the population density of the area which also gave a
picture of how the settlement of subscribers were found. The distance between sites depends
solely on the population density distribution. Antenna placement on cell tower considered again
the distribution of the population density of the area and the geographical hindrance if any.
Having a proper antenna orientation to subscriber’s daily activity areas and their settlement
places also gave a better point into coverage and performance evaluation.
Capacity estimation was another key feature in determining the coverage of the network and its
performance. Unlike 2G network 3G network capacity and coverage where planned together at
the same time. The observation revealed that it’s not possible to separate the two, by planning for
coverage and then capacity later on. For the network to work effectively both capacity and
coverage were dependent on each other while planning. Capacity estimation also depends on the
population density. Sectoring of the antenna was done with consideration of how the population
is distributed. The number of resources available was a criteria for capacity prediction. The
definition of bandwidth usage and channel allocation appeared to have a strong impact on
capacity estimation. The problems like dropped calls were largely minimized through proper
capacity estimation by considering the resources at hand.
Another very important aspect which contributed significantly in improving coverage was site
neighbouring planning. The site neighbouring planning gave a clearer picture of how resource
are distributed, shared and managed. It was the key in minimizing the handover failure while
subscribers communicated.
84
Network evaluation and analysis through basic predefined key performance indicators were
carried with the help of the QoS schemes. The schemes were first evaluated on their strength and
weakness and it was found that in the case of Fault Tolerant Dynamic channel Allocation
Scheme it was possible to reuse the channel and hence was suitable for reducing traffic
congestion in the network. Therefore the issue of channel capacity depends on this scheme. Next
Call was Admission Control Scheme used to avoid the bottleneck of the incoming calls and
hence it reduces the rate of blocking probability. The capacity related problems can be
minimized through the use of this scheme, then we had Mobility Prediction Scheme, which
collected the subscriber’s information who are moving from one point to another and then it
store them into the database. The collected information was used to prepare resources when there
was handover. This was very important to be highlighted in site neighbouring plan. Lastly, we
had a Dynamic Allocation Scheme using Renegotiation which made sure that the low priority
services do not starve and can be served at any time without affecting the QoS of high priority
services. It distributes the unused resource for low priority services and takes them when needed
without causing much effect since the low priority didn’t need those resources even though it
gave them since they were idle resources. The capacity planning came into effect in this scheme.
And all these schemes depends on one another in their operation.
When the QoS where analysed based on the data collected through drive test measurements at
first there were problems in every category, There were high number of call drops, blocking
calls, handover failure, poor quality and bad coverage for the entire sample area, Through this
analysis the optimisation was done and for the new sites which were constructed after proper
planning were considered all necessary factors like improving coverage, capacity and QoS, then
another analysis were performed to confirm the results. The new analysis based on the
85
benchmarking data for all the operators in the area of interest. The data revealed the high level of
improvement where the area with good coverage improved from being 24.02% to 57.40%, the
good quality moved from 27.61% to 32.60%, voice services at first had almost 33% of CSSR
and 67% of CDR. The new results revealed the overall voice performance of 92.65% with 100%
of the CSSR and there were no call drops or call blocking for all the attempted calls, and no
handover failure.
This research proves that, it is possible to improve coverage, especially in rural areas which is
less marketable area compared to urban areas. What is needed is proper network planning from
the initial stage. Good coverage helps in resource effective utilization and maximum
performance efficiency of the network.
5.3. General Recommendations
At the beginning of 2014, the government announced a major plan to empower the mobile
operators by providing funds so as they can build their infrastructure into less marketable wards
in the country. The government disbursed a total of $ 10milion to TTCL, TIGO, VODACOM
and AIRTEL through TCRA.
Due to the need of sharing resources, TCRA should put a rule that instead of finding both
companies in one place, then whenever let’s say company X has put the resources in a certain
area, then all the remaining companies should use all the resources of company X instead of
building the resources of their own. This will enable larger areas to be covered than it was
anticipated.
Use of an experienced and skilled radio engineers in early stages of planning. These mobile
operators usually outsource their work into other companies. It's time to review the experience
and skills of the company they outsource their work to, because there are some places the
86
problems are due to either poor planning and designing or bad installation of equipment due to
lack of sufficient knowledge with the growing technology.
87
REFERENCES
[1] Jianchang Yang, D. Manivannan, and Mukesh Singhal. A Fault-Tolerant Dynamic Channel
Allocation Scheme for Enhancing QoS in Cellular Networks. In IEEE Proceedings of the 36th
Hawaii International Conference on System Sciences (HICSS-36), Big Island of Hawaii, January
6-9, 2003, pages 306.
[2] Satya Kovvuri1, Vijoy Pandey2, Dipak Ghosal2, Biswanath Mukherjee2 and Dilip Sarkar1,
"A Call-Admission Control (CAC) Algorithm for Providing Guaranteed QoS in Cellular
Networks,"
[3] Wee-Seng Soh and Hyong S. Kim, "QoS Provisioning in Cellular Networks Based on
Mobility Prediction Techniques,"
[4] Hermes Irineu Del Monego1, Eliane Lucia Bodanese2, Luiz Nacamura Jr1, and Richard
Demo Souza1, "A Dynamic Resource Allocation Scheme for Providing QoS in Packet-Switched
Cellular Networks,"
[5] Kajackas A., Batkauskas V., Medeisis A , "Individual QoS Rating for Voice Services in
Cellular Networks
[6] Fei Yu, Vincent W.S Wong and Victor C.M Leung, "A New QoS Provisioning Method for
Adaptive Multimedia in Cellular Wireless Networks,"
[7] T. Rachidi, M. Sebbane, A.Y. Elbatji and H. Bouzekri , "An Integrated System for QoS
Provisioning in 3G WCDMA Cellular Networks,"
[8] M. Fry et al., QoS management in a World Wide Web environment which supports
continuous media, Distrib. Syst. Engineering, vol. 4, pp. 38–47, 1997.
[9] J. Koistinen and A. Seetharaman, Worth-Based Multi-Category Qualityof- Service
Negotiation in Distributed Object Infrastructures HP Research Report HPL-98-51, Hewlett
Packard, 1998.
[10] L. Delgrossi et al., Reservation Protocols for Internetworks: A Comparison of ST-II and
RSVP, Proc. of Network and Operating System Supportfor Digital Audio and Video, Sept. 1993,
pp. 195–203.
[11] M. Degermark, et al., Advance Reservations for Predictive Service, Proc. of Network and
Operating Systems Support for Digital Audio and Video, 1995.
[12] D. Ferrari, A. Gupta, and V. Giorgio, Distributed Advance Reservation of Real-Time
Connections, Multimedia Systems, vol. 5, 1997, pp. 187–98.
88
[13] C. J. Sreenan and P. P. Mishra, Equus: A QoS Manager for Distributed Applications, Proc.
IFIP/IEEE Int’l Conf. on Distributed Platforms, Dresden, 1996, pp. 496–509.
[14] A. Campbell, and G. Coulson, A QoS Adaptive Multimedia Transport System: Design,
Implementation and Experiences, Media Distrib. Syst.Engineering, vol. 4, 1997, pp. 48–58.
[15] L. J. N. Franken and B. R. H. M. Haverkort, Quality of Service Management Using Generic
Modelling and Monitoring Techniques, Distrib. Syst.Engineering, vol. 4, 1997, pp. 28–37.
[16] M. Billot et al., A Proposal for Ensuring High Availability of Distributed Multimedia
Applications, Proc. of 15th Symp. on Reliable DistributedSystems, 1996, pp. 220–27.
[17] Knightly, E.W., Rossaro, P., On the effects of smoothing for deterministic QoS Distrib.
Syst. Eng vol. 4 pp. 3–15 (IOP Publishing, 1997.
[18] Zhang, H., Knightly, E.W., RED-VBR: a renegotiation-based approach to support delay-
sensitive VBR video Multimedia Systems vol. 5 pp. 164–176 (Springer-Verlag, 1997.
[19]Azzedine Boukerche, Sungbum Hong, and Tom Jacob. A Distributed Algorithm for
Dynamic Channel Allocation. Mobile Networks and Applications, 7:115{126, 2002.
[20] Guohong Cao and Mukesh Singhal. An Adaptive Distributed Channel Allocation Strategy
for Mobile Cellular Networks. Journal of Parallel and Distributed Computing, special issue on
Mobile Computing, 60(4):451{473, April 2000.
[21] Guohong Cao and Mukesh Singhal. Distributed Fault-Tolerant Channel Allocation for
Cellular Networks. IEEE journal on selected areas in communications, 18(7):1326{1337, JULY
2000.
[22]Jianchang Yang, Q. Jiang, D. Manivannan, and M. Singhal. A Fault-Tolerant Distributed
Channel Allocation Scheme for Cellular Networks. IEEE Transactions on Computers,
54(5):616{629, 2005.
[23] Jianchang Yang and D. Manivannan. An E_cient Fault-Tolerant Distributed Channel
Allocation Algorithm for Mobile Computing Systems. In Proceedings of the Third International
Conference on Parallel and Distributed Computing, Applications, and Technologies
(PDCAT2002), Sept.4-6, 2002, Kanazawa, Japan, pages 372{377.
[24] Jianchang Yang and D. Manivannan. A Fault-Tolerant Channel Allocation Algorithm for
Cellular Networks with Mobile Base Stations. In Proceedings of the 2003 International
Conference on Wireless Networks(ICWN'03), Las Vegas, Nevada, USA, (CSREA Press) June
23-26, pages 146{152, 2003.
89
[25] S. Dixit, Y. Guo, and Z. Antoniou, “Resource management and quality of service in third
generation wireless networks,” IEEE Commun. Mag., vol. 39, no. 12, pp. 125–133, Feb. 2001.
[26] S. I. Maniatis, E. G. Nikolouzou, and I. S. Venieris, “QoS issues in the coverged 3G
wireless and wired networks,” IEEE Commun. Mag., vol. 40, pp. 44–53, Aug. 2002.
[27] O. Sallent, J. Perez-Romero, R. Agusti, and F. Casadevall, “Provisioning multimedia
wireless networks for better QoS: RRM strategies for 3G W-CDMA,” IEEE Commun. Mag.,
vol. 41, pp. 100–106, Feb. 2003. [6] S.-C. Lo, G. Lee, W.-T. Chen, and J.-C. Liu, “Architecture
for mobility and QoS support in all-IP wireless networks,” IEEE J. Sel. AreasCommunication.,
vol. 22, pp. 691–705, May 2004.
[28] D. Levine, I. Akyildiz, and M. Naghshineh, “A resource estimation and call admission
algorithm for wireless multimedia networks using the shadow cluster concept,” in IEEE/ACM
Trans. Netw., vol. 5, Feb. 1997, pp. 1–12.
[29] B. M. Epstein and M. Schwartz, “Predictive QoS-based admission control for multiclass
traffic in cellular wireless networks,” IEEE J. Sel.Areas Commun., vol. 18, no. 3, pp. 523–534,
Mar. 2000.
[30] B. Li, L. Yin, K. Y. M. Wong, and S. Wu, “An efficient and adaptive bandwidth allocation
scheme for mobile wireless networks based on on-line local parameter estimations,”
ACM/Baltzer J. Wireless Netw., vol. 7, pp. 107–116, Mar./Apr. 2001.
[31] Y. Cheng andW. Zhuang, “DiffServ resource allocation for fast handoff in wireless mobile
Internet,” IEEE Commun. Mag., vol. 40, pp. 130–136, May 2002.
[32] Blaunstein N, Censor D, Katz D, et al. (2003) Radio propagation in rural residential areas
with vegetation. Progress In Electromagnetics Research 40: 131-153.
[33] Dawy Z, Davidovic S and Oikonomidis I. (2003) Coverage and capacity enhancement of
CDMA cellular systems via multihop transmission. Global Telecommunications
Conference, 2003. GLOBECOM'03. IEEE. IEEE, 1147-1151.
[34] Forlin M, Larcher R and Schivo S. (2008) Review of current use of mobile telephony in
developing regions.
[35] Guo L, Zhang J and Maple C. (2003) Coverage and Capacity Calculations for 3G Mobile
Network Planning. University of Luton, UK: PGNet.
[36] Hurley S. (2002) Planning effective cellular mobile radio networks. Vehicular Technology,
IEEE Transactions on 51: 243-253.
90
[37] Kajackas A, Batkauskas V, Saltis A, et al. (2011) Autonomous System for Observation of
QoS in Telecommunications Networks. Electronics and Electrical Engineering 111: 15-
18.
[38] Khattar V. (2006) QoS and CustomerSatisfaction: A Stud. PipelinePub.com Volume 3
[39] Rashid AT and Elder L. (2009) Mobile phones and development: An Analysis of IDRC-
supported projects. The Electronic Journal of Information Systems in Developing
Countries 36.
[40] Sife AS, Kiondo E and Lyimo-Macha JG. (2010) Contribution of mobile phones to rural
livelihoods and poverty reduction in Morogoro Region, Tanzania. The Electronic Journal
of Information Systems in Developing Countries 42.
[41] Tacchi JA, Slater D and Hearn GN. (2003) Ethnographic action research: A user’s
handbook.
[42] Tutschku K, Gerlich N and Tran-Gia P. (1996) An integrated approach to cellular network
planning. Proceedings of the 7th International Network Planning Symposium (Networks
96). Citeseer, 185-190.
[43] TCRA (Tanzania Communications Regulatory Authority) (2006) Market Information.
http://www.tcra.go.tz/Market.
[44] TCRA (Tanzania Communications Regulatory Authority) (June,2014) Market Information.
http://www.tcra.go.tz/Market.
[45] Sood, A.D (2006) the Mobile Development Report: The Socio-Economic Dynamics of
Mobile Communications in Rural Areas and their Consequences for Development.
http://cks.in/mdr/Mobile%20Development%20Report_updated.pdf.
[46] Souter, D., Scott, N., Garforth, C., Jain, R., Mascarenhas, O. and McKemey, K (2005) The
Economic Impact of Telecommunications on Rural Livelihoods and Poverty Reduction: A Study
of Rural Communities in India (Gujarat), Mozambique and Tanzania. Report of DFID KaR.
[47] ITU (International Telecommunication Union) (2006) World Telecommunication/ICT
Development Report 2006: Measuring ICT for Social and Economic Development. ITU,
Geneva.
[48] ITU (International Telecommunication Union) (2012) World Telecommunication/ICT
Development Report 2012: Measuring the information society 2012. ITU, Geneva.
91
[49]The Economist. 2008. “Halfway There: How to promote the spread of mobile phones among
the world's poorest.” May 29, 2008.
[50] A. T. Kasegenya, Dr. A. Sam, “Review of Schemes for Analyzing Quality of Service in
Wireless Network Environment”, Conference Proceedings of the Pan African Conference on
Science, Computing and Telecommunications (PACT 2014), July 14 -18, 2014, Arusha –
Tanzania.
[51] Bo Hagerman, Davide Imbeni and Jozsef Barta “WCDMA 6 – sector Deployment-Case
Study of a Real Installed UMTS-FDD Network” IEEE Vehicular Technology Conference,
spring 2006, page(s): 703 - 707.
[52] S. Sharma, A.G. Spilling and A.R. Nix “Adaptive Coverage for UMTS Macro cellsbased on
Situation Awareness”. IEEE Vehicular Technology Conference, spring 2001, page(s):2786 -
2790
[53] A. Wacker, J. Laiho-Steffens, K. Sipila, K. Heiska, "The impact of the base station
sectorisation on WCDMA radio network performance", IEEE Vehicular Technology Conference
,September 1999,page(s): 2611 - 2615 vol.5.
[54] Romeo Giuliano, Franco Mazzenga, Francesco Vatalaro, “Adaptive cell sectorization for
UMTS third generation CDMA systems” IEEE Vehicular Technology Conference, May
2001,page(s): 219 - 223 vol.1.
[55] T.S.Rappaport, “Wireless Communications Principles and Practice”-Second Edition,
Prentice Hall.
[56] Bernard Sklar, “Digital Communications - Fundamentals and Applications”- Second
Edition Prentice Hall.
[57] Ingo Fo, Marc Schinnenburg, Bianca Wouters “Performance Evaluation of Soft Handover in
a Realistic UMTS Network”, IEEE Vehicular Technology Conference, Spring 2003, Page(s):
1979 - 1983 VOL.3.
[58] Harri Holma and Antti Toskala, “WCDMA for UMTS-Radio Access Third Generation
Mobile Communications”- John Wiley & Sons.
[59] Jaana Laiho, Achim Wacker, Tomas Novosad, “Radio Network Planning and Optimization
for UMTS”-Second Edition John Wiley & Sons.
[60] A. Skopljak, “Multiantenna CDMA systems and their usage in 3G network”, University of
Sarajevo, 2007.
92
[61]Faruque, Saleh, “Cellular Mobile System Engineering”, Artech House Publishers, 1996.
[62] Jhong Sam Lee, Leonard E. Miller, “CDMA Systems Engineering Handbook”-Artech
House Publishers.
[63] Koushik Majumder, Subir Kumar Sarkar” Performance Analysis of AODV and DSR
Routing Protocols in Hybrid Network Scenario”IEEE Xplore
[64] C. K. Toh, Associativity-Based Routing for Ad Hoc Mobile Networks, Wireless Personal
Communications, vol. 4, no. 2, pp. 136, March 1997.
[65] R. S. Sisodia, B. S. Manoj, and C. Siva Ram Murthy, A Preferred Link- Based Routing
Protocol for Ad Hoc Wireless Networks, Journal of Communications and Networks, vol. 4, no.
1, pp. 14-21, March 2002.
[66] “A Survey of Context-Aware Mobile Computing Research”, Guanling Chen and David
Kotz, Dartmouth Computer Science Technical Report TR2000-381
[67] Barry Brumitt, Brian Meyers, John Krumm, Amanda Kern, and Steven Shafer. EasyLiving:
Technologies for intelligent environments. In Proceedings of Second International Symposium
on Handheld and Ubiquitous Computing, HUC 2000, pages 12-29, Bristol, UK, September 2000.
Springer Verlag.
[68] Peter J. Brown. Triggering information by context. Personal Technologies, 2(1), March
1998.
[69] Mummert, L.B., Satyanarayanan, M. Large Granularity Cache Coherence for Intermittent
Connectivity. In Proceedings of the 1994 Summer USENIX Conference. Boston, MA, June,
1994.
[70] http://stupidcaterpillar.wordpress.com/2011/02/03/rscp-eci0/
[71] EISENBLATTER, A., GEERDES, H.-F. & GROTSCHEL, M. 2008. Planning UMTS radio
networks. OR/MS Today, 35, 41-46.
[72] GLISIC, S. G. 2003. CDMA network. Adaptive WCDMA: Theory and Practice, 217-270.
[73] GUO, L., ZHANG, J. & MAPLE, C. 2003. Coverage and Capacity Calculations for 3G
Mobile Network Planning. proc. PGNET2003, June, 16-17.
[74] HODGE, L. E. 2006. Cell density requirements for UMTS network planning. International
Journal of Mobile Network Design and Innovation, 1, 279-288.
93
[75] HOLMA, H., HONKASALO, Z.-C., HAMALAINEN, S., LAIHO, J., SIPILA, K. &
WACKER, A. 2010. Radio Network Planning. WCDMA for UMTS: HSPA Evolution and
LTE, 173.
[76] HURTADO, A. F. C. October 2005. UMTS Capacity simulation study. Master of Science in
Telematics, University of Twente
[77] KUMAR, A., LIU, D. Y. & SENGUPTA, J. 2010. Divya,“Evolution of Mobile Wireless
Communication Networks 1G to 4G”. International Journal of Electronics &
Communication Technology, IJECT, 1.
[78] LAIHO, J. 2002. Radio network planning and optimisation for WCDMA, Helsinki
University of Technology.
[79] LAIHO, J., WACKER, A. & NOVOSAD, T. 2006. Radio network planning and
optimisation for UMTS, John Wiley & Sons.
[80] MAHATO, S. B. 2007. Performance Evaluation of Six-Sectored Configuration in
Hexagonal WCDMA (UMTS) Cellular Network Layout.
[81] SIPILA, K., LAIHO-STEFFENS, J., WACKER, A. & JASBERG, M. Modeling the impact
of the fast power control on the WCDMA uplink. Vehicular Technology Conference,
1999 IEEE 49th, 1999. IEEE, 1266-1270.
[82] TOSKALA, A., HOLMA, H., KOLDING, T., FREDERIKSEN, F. & MOGENSEN, P.
2001. WCDMA for UMTS: Radio Access for Third Generation Mobile Communications,
Wiley England.
[83]Ojanperä, T. and Prasad, R., Wideband CDMA for Third Generation Mobile
Communications, Artech House, 1998.
[84] Saunders, S., Antennas and Propagation for Wireless Communication Systems, John Wiley
& Sons, 1999.
[85] Wacker, A., Laiho-Steffens, J., Sipilä, K. and Heiska, K., ‘The Impact of the Base Station
Sectorisation on WCDMA Radio Network Performance’, Proceedings of VTC'99, Houston,
Texas, May 1999, pp. 2611–2615.
[86] Sipilä, K., Honkasalo, Z., Laiho-Steffens, J. and Wacker, A., ‘Estimation of Capacity and
Required Transmission Power of WCDMA Downlink Based on a Downlink Pole Equation’,
to appear in Proceedings of VTC2000, Spring 2000.
[87] Lee, J. and Miller, L., CDMA Systems Engineering Handbook, Artech House, 1998.
94
[88] Wacker, A., Laiho-Steffens, J., Sipilä, K. and Jäsberg, M., ‘Static Simulator for Studying
WCDMA Radio Network Planning Issues’, Proceedings of VTC'99, Houston, Texas, May
1999, pp. 2436–2440.